qid
stringclasses 150
values | question
stringlengths 43
393
| answer
stringlengths 1
623
| data_source
stringclasses 1
value | prompt
listlengths 1
1
| ability
stringclasses 1
value | reward_model
dict | extra_info
dict |
|---|---|---|---|---|---|---|---|
0
|
Can you inform me who are the authors of "Patient-Specific Physiological Monitoring And Prediction Using Structured Gaussian Processes?"?
|
Yang Yang, Chris Pugh, Kate Niehaus, Clare MacEwen, Glen W. Colopy, D Clifton, Tingting Zhu
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you inform me who are the authors of \"Patient-Specific Physiological Monitoring And Prediction Using Structured Gaussian Processes?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Yang Yang, Chris Pugh, Kate Niehaus, Clare MacEwen, Glen W. Colopy, D Clifton, Tingting Zhu"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 0,
"split": "train"
}
|
1
|
Can you inform me who are the authors of "Long Range Optical Truck Tracking.?"?
|
Dietrich Paulus, Christian Winkens
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you inform me who are the authors of \"Long Range Optical Truck Tracking.?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Dietrich Paulus, Christian Winkens"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 1,
"split": "train"
}
|
2
|
Can you inform me who are the authors of "0.33 mm 2 13.3 dB gain sub-6 GHz to 28 GHz transformer-coupled low-voltage upconversion mixer for 5G applications?"?
|
Oner Hanay, Renato Negra
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you inform me who are the authors of \"0.33 mm 2 13.3 dB gain sub-6 GHz to 28 GHz transformer-coupled low-voltage upconversion mixer for 5G applications?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Oner Hanay, Renato Negra"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 2,
"split": "train"
}
|
3
|
Could you tell me the authors of the paper "Physical parameter extraction over urban areas using L-band POLSAR data and interferometric baseline diversity?"?
|
Stefan Sauer, Eric Pottier, Laurent Ferro-Famil, Andreas Reigber
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCould you tell me the authors of the paper \"Physical parameter extraction over urban areas using L-band POLSAR data and interferometric baseline diversity?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Stefan Sauer, Eric Pottier, Laurent Ferro-Famil, Andreas Reigber"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 3,
"split": "train"
}
|
4
|
Who are the authors of paper "A New Node Deployment and Location Dispatch Algorithm for Underwater Sensor Networks.?"?
|
Lurong Jiang, Peng Jiang, Binfeng Ruan, Jun Liu, Feng Wu
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWho are the authors of paper \"A New Node Deployment and Location Dispatch Algorithm for Underwater Sensor Networks.?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Lurong Jiang, Peng Jiang, Binfeng Ruan, Jun Liu, Feng Wu"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 4,
"split": "train"
}
|
5
|
Who are the authors of paper "Distributed global development parametric cost modeling?"?
|
Raymond J. Madachy
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWho are the authors of paper \"Distributed global development parametric cost modeling?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Raymond J. Madachy"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 5,
"split": "train"
}
|
6
|
Could you tell me the authors of the paper "BlockHammer: Improving Flash Reliability by Exploiting Process Variation Aware Proactive Failure Prediction?"?
|
Fei Wu, Wenmin Zhong, Qiulin Wu, Changsheng Xie, Zhonghai Lu, Ruixiang Ma, Jiguang Wan
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCould you tell me the authors of the paper \"BlockHammer: Improving Flash Reliability by Exploiting Process Variation Aware Proactive Failure Prediction?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Fei Wu, Wenmin Zhong, Qiulin Wu, Changsheng Xie, Zhonghai Lu, Ruixiang Ma, Jiguang Wan"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 6,
"split": "train"
}
|
7
|
Can you tell me who wrote the paper "Biologically Inspired Neural Controller For Robot Learning And Mapping?"?
|
Alejandra Barrera Ramirez, Alfredo Weitzenfeld Ridel
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me who wrote the paper \"Biologically Inspired Neural Controller For Robot Learning And Mapping?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Alejandra Barrera Ramirez, Alfredo Weitzenfeld Ridel"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 7,
"split": "train"
}
|
8
|
Can you tell me who wrote the paper "Sub-Bottom Sediment Classification Using Reliable Instantaneous Frequency Calculation and Relaxation Time Estimation?"?
|
Hongmei Zhang, Jianhu Zhao, Shaobo Li, Siheng Qu
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me who wrote the paper \"Sub-Bottom Sediment Classification Using Reliable Instantaneous Frequency Calculation and Relaxation Time Estimation?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Hongmei Zhang, Jianhu Zhao, Shaobo Li, Siheng Qu"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 8,
"split": "train"
}
|
9
|
Could you tell me the authors of the paper "Robust assembly line balancing with heterogeneous workers?"?
|
Jean-François Cordeau, Gilbert Laporte, Mayron César O. Moreira, Alysson M. Costa
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCould you tell me the authors of the paper \"Robust assembly line balancing with heterogeneous workers?\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Jean-François Cordeau, Gilbert Laporte, Mayron César O. Moreira, Alysson M. Costa"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 9,
"split": "train"
}
|
10
|
What organization is researcher Justin Booth-Clibborn affiliated with?
|
New York, New York
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhat organization is researcher Justin Booth-Clibborn affiliated with?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "New York, New York"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 10,
"split": "train"
}
|
11
|
What organization is researcher Greg Daville affiliated with?
|
Hove East Sussex, United Kingdom
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhat organization is researcher Greg Daville affiliated with?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Hove East Sussex, United Kingdom"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 11,
"split": "train"
}
|
12
|
Which organization does researcher Kohta Morie belong to?
|
Transistor Studio, Japan
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhich organization does researcher Kohta Morie belong to?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Transistor Studio, Japan"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 12,
"split": "train"
}
|
13
|
Can you tell me the affiliation of the researcher Coke Ferreiro?
|
Spain
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me the affiliation of the researcher Coke Ferreiro?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Spain"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 13,
"split": "train"
}
|
14
|
Can you tell me the affiliation of the researcher C. A. Petri?
|
GMD Bonn Germany Germany
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me the affiliation of the researcher C. A. Petri?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "GMD Bonn Germany Germany"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 14,
"split": "train"
}
|
15
|
Can you tell me the affiliation of the researcher Nikita Deshpande?
|
DSK Supinfocom, Pune
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me the affiliation of the researcher Nikita Deshpande?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "DSK Supinfocom, Pune"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 15,
"split": "train"
}
|
16
|
Which institution is the researcher Franz Von Kutschera associated with?
|
Philosophische FakultÄt I UniversitÄt Regensburg UniversitÄtstrasse 31 Postfach 397 8400 Regensburg Germany
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhich institution is the researcher Franz Von Kutschera associated with?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Philosophische FakultÄt I UniversitÄt Regensburg UniversitÄtstrasse 31 Postfach 397 8400 Regensburg Germany"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 16,
"split": "train"
}
|
17
|
Can you tell me the affiliation of the researcher Marcin Kobylecki?
|
Warszawa, Poland
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nCan you tell me the affiliation of the researcher Marcin Kobylecki?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Warszawa, Poland"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 17,
"split": "train"
}
|
18
|
Which organization does researcher Theo D’Hondt belong to?
|
Vrije Universiteit Brussel Belgium
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhich organization does researcher Theo D’Hondt belong to?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Vrije Universiteit Brussel Belgium"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 18,
"split": "train"
}
|
19
|
Which institution is the researcher Arthur Lemmens associated with?
|
Amsterdam
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhich institution is the researcher Arthur Lemmens associated with?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Amsterdam"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 19,
"split": "train"
}
|
20
|
Where is the paper "Scalable Lossless And Lossy Image Coding Based On The Rwhat Plus P Pyramid And The Inter-Coefficient Classification Method" published?
|
2008 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhere is the paper \"Scalable Lossless And Lossy Image Coding Based On The Rwhat Plus P Pyramid And The Inter-Coefficient Classification Method\" published?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "2008 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-4"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 20,
"split": "train"
}
|
21
|
In which place was the paper "A method for sub-sample computation of time displacements between discrete signals based only on discrete correlation sequences." published?
|
Biomedical Signal Processing and Control
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nIn which place was the paper \"A method for sub-sample computation of time displacements between discrete signals based only on discrete correlation sequences.\" published?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Biomedical Signal Processing and Control"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 21,
"split": "train"
}
|
22
|
What is the publication location for the paper "Private sector needs for trusted/secure computer systems"?
|
AFIPS National Computer Conference
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhat is the publication location for the paper \"Private sector needs for trusted/secure computer systems\"?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "AFIPS National Computer Conference"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 22,
"split": "train"
}
|
23
|
In which place was the paper "Design Of Ring Oscillator Structures For Measuring Isolated Nbti And Pbti" published?
|
2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012)
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nIn which place was the paper \"Design Of Ring Oscillator Structures For Measuring Isolated Nbti And Pbti\" published?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012)"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 23,
"split": "train"
}
|
24
|
In which place was the paper "Cooperative Aerial Manipulation with Decentralized Adaptive Force-Consensus Control" published?
|
Journal of Intelligent & Robotic Systems
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nIn which place was the paper \"Cooperative Aerial Manipulation with Decentralized Adaptive Force-Consensus Control\" published?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Journal of Intelligent & Robotic Systems"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 24,
"split": "train"
}
|
25
|
Where has the paper "On the evaluation of the Eigenvalues of a banded toeplitz block matrix" been published?
|
Journal of Complexity
|
grbench
|
[
{
"content": "Solve a question answering task by repeating bundled steps that contain reasoning (<think>...</think>) followed by exactly one graph interaction (<graph>...</graph>). After each <graph> call, the environment returns feedback inside <information>...</information>. You may take as many steps as necessary.\n\nOutput protocol (bundled steps):\n- Intermediate step (must include BOTH in a single output, in this order):\n <think>...</think><graph>Function[...]</graph>\n (Then the environment responds with <information>...</information>.)\n- Final step (no more graph calls):\n <think>...</think><answer>...</answer>\n \nAvailable graph interaction functions (use exactly these names and signatures INSIDE <graph>...):\n- RetrieveNode[keyword] # retrieves the related node from the graph according to the query\n- NodeFeature[Node, feature] # returns detailed attribute information of Node for the given \"feature\" key\n- NodeDegree[Node, neighbor_type] # returns the number of \"neighbor_type\" neighbors of Node\n- NeighbourCheck[Node, neighbor_type] # lists the \"neighbor_type\" neighbors of Node and returns them\n\nRules and format:\n1) You MUST conduct reasoning inside <think>...</think> before every graph call and after every <information> you receive.\n2) Inside <graph>...</graph>, issue EXACTLY ONE function from the list below per step. Do NOT include any other text in <graph>.\n3) Do NOT fabricate <information>; it is ONLY produced by the environment immediately after your <graph> step.\n4) Keep thoughts concise and ONLY inside <think>. Do NOT put a graph call inside <think>, and do NOT put thoughts inside <graph>.\n5) The final output MUST contain ONLY one <answer>...</answer> block with the requested node main features (e.g., names), not node IDs.\n\nHere are some examples:\nDefinition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What organization is researcher Greg Daville from?\n <think>The question is asking about the organization of a researcher named Greg Daville. We need to find the node corresponding to Greg Daville in the graph.</think><graph>RetrieveNode[Greg Daville]</graph>\n <information>The ID of this retrieval target node is 53f460a7dabfaee4dc83702a.</information>\n <think>The question is asking for the organization of a researcher, so we need to check the node's organization feature from the graph.</think><graph>NodeFeature[53f460a7dabfaee4dc83702a, organization]</graph>\n <information>Hove East Sussex, United Kingdom </information>\n <think>The organization of researcher Greg Daville is Hove East Sussex, United Kingdom.</think><answer>Hove East Sussex, United Kingdom</answer> \n \n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: How many papers are written by author Nicholas Lydon?\n <think>The question is asking for the number of written papers of a specific author (Nicholas Lydon). We need to find the author node in the graph.</think><graph>RetrieveNode[Nicholas Lydon]</graph>\n <information>The ID of this retrieval target node is 53f438c3dabfaedf43596117.</information>\n <think>The question is asking for the number of papers written by Nicholas Lydon. We need to calculate the \"paper\" neighbor degree of this node.</think><graph>NodeDegree[53f438c3dabfaedf43596117, paper]</graph>\n <information>2</information>\n <think>The number of the paper neighbors is 2</think><answer>2</answer> \n\n Definition of the graph: There are three types of nodes in the graph: paper, author and venue.\n Paper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\n Paper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n Question: What was the publish venue of the paper Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars?\n <think>The question is asking information of a node (Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars). We need to find the node in the graph.</think><graph>RetrieveNode[Mass Accretion Rates in Self-Regulated Disks of T Tauri Stars]</graph>\n <information>The ID of this node is 2090642949.</information>\n <think>The question is asking the published venue of a paper, we need to check the node's venue neighbor from the graph.</think><graph>NeighbourCheck[2090642949, venue]</graph>\n <information>['1980519', '1053242']</information>\n <think>The ID of the published venue are 1980519 and 1053242. We need to get their names.</think><graph>NodeFeature[1980519, name]</graph>\n <information>the astrophysical journal</information>\n <think>We also need the name for 1053242.</think><graph>NodeFeature[1053242, name]</graph>\n <information>the atmosphere journal</information>\n <think>The name of the published venues are the astrophysical journal and the atmosphere journal</think><answer>the astrophysical journal, the atmosphere journal</answer>\n \n(END OF EXAMPLES)\n\nDefinition of the graph:\nThere are three types of nodes in the graph: paper, author and venue.\nPaper nodes have features: title, abstract, keywords, lang, and year. Author nodes have features: name and organization. Venue nodes have features: name.\nPaper nodes are linked to their author nodes, venue nodes, reference nodes (the papers this paper cite) and cited_by nodes (other papers which cite this paper). Author nodes are linked to their paper nodes. Venue nodes are linked to their paper nodes.\n\nQuestion:\nWhere has the paper \"On the evaluation of the Eigenvalues of a banded toeplitz block matrix\" been published?\n",
"role": "user"
}
] |
fact-reasoning
|
{
"ground_truth": {
"target": "Journal of Complexity"
},
"style": "rule"
}
|
{
"difficulty": "easy",
"domain": "dblp",
"index": 25,
"split": "train"
}
|
End of preview. Expand
in Data Studio
No dataset card yet
- Downloads last month
- 13