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list labels used
Browse files- interfaces/ner.py +2 -1
interfaces/ner.py
CHANGED
@@ -34,7 +34,8 @@ def named_entity_recognition(text, language):
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pipeline = huspacy.load() if model_id.startswith("hu") else spacy.load(model_id)
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doc = pipeline(text)
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entities = [{"entity":ent.label_, "start":ent.start_char, "end":ent.end_char} for ent in doc.ents]
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-
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output = {"text":text, "entities":entities}
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model_id_hf = f"huspacy/{model_id}" if model_id.startswith("hu") else f"spacy/{model_id}"
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output_info = legend + f'<p style="text-align: center; display: block">Prediction was made using the <a href="https://huggingface.co/{model_id_hf}">{model_id_hf}</a> model.</p> <ul> {" ".join(legend)} </ul>'
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pipeline = huspacy.load() if model_id.startswith("hu") else spacy.load(model_id)
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doc = pipeline(text)
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entities = [{"entity":ent.label_, "start":ent.start_char, "end":ent.end_char} for ent in doc.ents]
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labels_used = [ent.label_ for ent in doc.ents]
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legend = "<ul>"+"".join([f"<li> <b>{label}</b> = <i>{spacy.glossary.GLOSSARY[label]}</i> </li>" for label in set(labels_used)])+"</ul>"
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output = {"text":text, "entities":entities}
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model_id_hf = f"huspacy/{model_id}" if model_id.startswith("hu") else f"spacy/{model_id}"
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output_info = legend + f'<p style="text-align: center; display: block">Prediction was made using the <a href="https://huggingface.co/{model_id_hf}">{model_id_hf}</a> model.</p> <ul> {" ".join(legend)} </ul>'
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