Maria Tsilimos commited on
Commit
32a0edb
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1 Parent(s): 9fd1400

Update app.py

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Files changed (1) hide show
  1. app.py +3 -2
app.py CHANGED
@@ -35,8 +35,8 @@ expander = st.expander("**Important notes on the 4-Scandinavian Named Entity Rec
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  expander.write('''
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  **Named Entities:** This 4-Scandinavian Named Entity Recognition Web App predicts four (4) labels (“PER: person”, “LOC: location”, “ORG: organization”, “MISC: miscellaneous”). Results are presented in an easy-to-read table, visualized in an interactive tree map, pie chart, and bar chart, and are available for download along with a Glossary of tags.
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- **How to Use:** Paste a URL, and then press Enter. If you type or paste text, just press Ctrl + Enter.
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-
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  **Usage Limits:** You can request results up to 10 times.
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  **Customization:** To change the app's background color to white or black, click the three-dot menu on the right-hand side of your app, go to Settings and then Choose app theme, colors and fonts.
@@ -47,6 +47,7 @@ expander.write('''
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  ''')
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  with st.sidebar:
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  container = st.container(border=True)
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  container.write("**Named Entity Recognition (NER)** is the task of extracting and tagging entities in text data. Entities can be persons, organizations, locations, countries, products, events etc.")
 
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  expander.write('''
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  **Named Entities:** This 4-Scandinavian Named Entity Recognition Web App predicts four (4) labels (“PER: person”, “LOC: location”, “ORG: organization”, “MISC: miscellaneous”). Results are presented in an easy-to-read table, visualized in an interactive tree map, pie chart, and bar chart, and are available for download along with a Glossary of tags.
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+ **How to Use:** Upload your .pdf or .docx file. Then, click the 'Results' button to extract and tag entities in your text data.
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+
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  **Usage Limits:** You can request results up to 10 times.
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  **Customization:** To change the app's background color to white or black, click the three-dot menu on the right-hand side of your app, go to Settings and then Choose app theme, colors and fonts.
 
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  ''')
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+
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  with st.sidebar:
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  container = st.container(border=True)
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  container.write("**Named Entity Recognition (NER)** is the task of extracting and tagging entities in text data. Entities can be persons, organizations, locations, countries, products, events etc.")