import spacy
import gradio as gr


def make_ent_dict(list):
    ent_dict = {
    'ORG': '',
    'PERSON': '',
    'GPE': '',
    'DATE': '',
    'TIME': '',
    'MONEY': '',
    'PERCENT': '',
    'QUANTITY': '',
    'PRODUCT': '',
    }
    for item in list:
        if item[0] in ent_dict.keys():
            ent_dict[item[0]] = item[1]
    return ent_dict


def get_named_entity(text):
    nlp = spacy.load("en_core_web_sm")
    doc = nlp(text)
    ent_list = [(ent.label_, ent.text) for ent in doc.ents]
    return make_ent_dict(ent_list)


iface = gr.Interface(fn=get_named_entity, inputs="text", outputs="text")
iface.launch(inline=False)