| --- |
| configs: |
| - config_name: CA |
| data_files: |
| - split: test |
| path: |
| - Task1(CA).csv |
| - config_name: DS |
| data_files: |
| - split: test |
| path: |
| - Task2(DS).csv |
| - config_name: CQ |
| data_files: |
| - split: test |
| path: |
| - Task3(CQ).csv |
| - config_name: FiB |
| data_files: |
| - split: test |
| path: |
| - Task4(FiB).csv |
| - config_name: QNLI |
| data_files: |
| - split: test |
| path: |
| - Task5(QNLI).csv |
| - config_name: AWP |
| data_files: |
| - split: test |
| path: |
| - Task6(AWP).csv |
| license: mit |
| language: |
| - bn |
| pretty_name: BenNumEval |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
|
|
| # BenNumEval: A Benchmark to Assess LLM’s Numerical Reasoning Capabilities in Bengali |
|
|
| **BenNumEval** is a novel benchmark designed to evaluate the numerical reasoning abilities of Large Language Models (LLMs) in the Bengali language. It introduces six diverse task categories and a high-quality dataset containing over 3,200 examples derived from educational and real-world sources. |
|
|
| ## 📁 Dataset Overview |
|
|
| BenNumEval includes **3,255** curated examples divided into six task types: |
|
|
| | Task Type | Description | Examples | |
| |-------------------------------|-----------------------------------------------------------------------------|----------| |
| | Commonsense + Arithmetic (CA) | Problems combining arithmetic with common-sense knowledge | 410 | |
| | Domain-Specific (DS) | Problems requiring domain knowledge (e.g., physics, chemistry, CS) | 705 | |
| | Commonsense + Quantitative (CQ) | Simple comparisons based on everyday logic | 400 | |
| | Fill-in-the-Blanks (FiB) | Arithmetic word problems in fill-in-the-blank style | 665 | |
| | Quantitative NLI (QNLI) | Natural language inference involving numerical understanding | 425 | |
| | Arithmetic Word Problems (AWP)| Real-world word problems requiring arithmetic reasoning | 650 | |
|
|
|
|
| # Code Snipet to Download the dataset |
|
|
| Install the datasets library if you've not installed yet. |
| ``` |
| pip install datasets |
| ``` |
|
|
| Then load the dataset |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("ka05ar/BenNumEval", 'CA') #for downloading Task1(CA) subset |
| ``` |
|
|
| ## 📜 Citation |
|
|
| If you use **BenNumEval** in your work, please cite: |
|
|
| ```bibtex |
| @inproceedings{ahmed2025bennumeval, |
| title={BenNumEval: A Benchmark to Assess LLMs’ Numerical Reasoning Capabilities in Bengali}, |
| author={Ahmed, Kawsar and Osama, Md and Sharif, Omar and Hossain, Eftekhar and Hoque, Mohammed Moshiul}, |
| booktitle={Findings of the Association for Computational Linguistics: ACL 2025}, |
| pages={17782--17799}, |
| year={2025} |
| } |
| ``` |
