saritha5 commited on
Commit
c86f45b
·
1 Parent(s): dd9664c

Update app.py

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Files changed (1) hide show
  1. app.py +12 -14
app.py CHANGED
@@ -16,8 +16,8 @@ def main():
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  spacy_model = "en_core_web_sm"
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  st.title('Entity Extraction')
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- menu = ["Home","NER"]
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- choice = st.sidebar.selectbox("Menu", menu)
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  with st.sidebar:
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  st.write("Sample Text")
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  st.write("""Ai-Khanoum (/aɪ ˈhɑːnjuːm/, meaning Lady Moon; Uzbek: Oyxonim) is the archaeological site of a Hellenistic city in Takhar Province, Afghanistan.
@@ -27,19 +27,17 @@ archaeologists until the outbreak of conflict in Afghanistan in the late 1970s.
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  st.write("""The Indian Space Research Organisation or is the national space agency of India, headquartered in Bengaluru.
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  It operates under Department of Space which is directly overseen by the Prime Minister of India while Chairman of ISRO acts as executive of DOS as well.""")
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- if choice == "Home":
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- st.subheader("Tokenization")
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- raw_text = st.text_area("Your Text","Enter the Text Here")
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- docx = nlp(raw_text)
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- if st.button("Tokenize"):
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- spacy_streamlit.visualize_tokens(docx,attrs = ['text','pos_','dep_','ent_type_'])
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-
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- elif choice == 'NER':
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- st.subheader("Name Entity Recognition")
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- raw_text = st.text_area("Your Text","Enter the Text Here")
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- docx = nlp(raw_text)
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  spacy_streamlit.visualize_ner(docx,labels = nlp.get_pipe('ner').labels,show_table = False)
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- #displacy.render(docx,style="ent")
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  spacy_model = "en_core_web_sm"
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  st.title('Entity Extraction')
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+ #menu = ["Home","NER"]
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+ #choice = st.sidebar.selectbox("Menu", menu)
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  with st.sidebar:
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  st.write("Sample Text")
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  st.write("""Ai-Khanoum (/aɪ ˈhɑːnjuːm/, meaning Lady Moon; Uzbek: Oyxonim) is the archaeological site of a Hellenistic city in Takhar Province, Afghanistan.
 
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  st.write("""The Indian Space Research Organisation or is the national space agency of India, headquartered in Bengaluru.
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  It operates under Department of Space which is directly overseen by the Prime Minister of India while Chairman of ISRO acts as executive of DOS as well.""")
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+ st.subheader("Tokenization")
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+ raw_text = st.text_area("Your Text","Enter the Text Here")
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+ docx = nlp(raw_text)
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+ if st.button("Tokenize"):
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+ spacy_streamlit.visualize_tokens(docx,attrs = ['text','pos_','dep_','ent_type_'])
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+
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+ st.subheader("Name Entity Recognition")
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+ if st.button("Entity Extraction"):
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+
 
 
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  spacy_streamlit.visualize_ner(docx,labels = nlp.get_pipe('ner').labels,show_table = False)
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+
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