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import spacy | |
import spacy_transformers | |
import gradio as gr | |
nlp = spacy.load("en_core_web_trf") | |
examples = [ | |
"Does Chicago have any stores and does Joe live here?", | |
] | |
def ner(text): | |
doc = nlp(text) | |
final_output = [] | |
for ent in doc.ents: | |
output = {'entity': ent.label_, 'word': ent.text, 'start': int(ent.start_char), 'end': int(ent.end_char)} | |
final_output.append(output) | |
return {"text": text, "entities": final_output} | |
demo = gr.Interface(ner, | |
gr.Textbox(placeholder="Enter sentence here..."), | |
gr.HighlightedText(), | |
examples=examples) | |
if __name__ == '__main__': | |
demo.launch(debug=True) |