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import streamlit as st |
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import spacy |
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from spacy import displacy |
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nlp = spacy.load("en_core_web_sm") |
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def visualize_entities(doc): |
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entities = [(ent.start_char, ent.end_char, ent.label_) for ent in doc.ents] |
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html = displacy.render(doc, style="ent", options={"ents": entities}) |
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st.markdown(html, unsafe_allow_html=True) |
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def filter_entities(entities, selected_labels): |
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if not selected_labels: |
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return entities |
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filtered_entities = [] |
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for entity, label in entities: |
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if label in selected_labels: |
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filtered_entities.append((entity, label)) |
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return filtered_entities |
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def main(): |
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st.title("Named Entity Recognition App") |
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st.write("Enter a text and get named entities!") |
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user_input = st.text_area("Enter text:", height=200) |
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visualize = st.checkbox("Visualize Entities") |
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filter_labels = st.multiselect("Filter Entities by Label:", options=["PERSON", "ORG", "GPE", "DATE"]) |
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if st.button("Analyze"): |
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doc = nlp(user_input) |
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entities = [(ent.text, ent.label_) for ent in doc.ents] |
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if visualize: |
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visualize_entities(doc) |
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filtered_entities = filter_entities(entities, filter_labels) |
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st.write("Named Entities:") |
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for entity, label in filtered_entities: |
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st.write(f"Text: {entity}, Entity: {label}") |
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if __name__ == "__main__": |
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main() |
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