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Update app.py

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  1. app.py +8 -7
app.py CHANGED
@@ -752,15 +752,16 @@ def create_interface():
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  gr.Markdown("""
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  # Named Entity Recognition (NER) Explorer Tool
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- Combine common NER categories with your own custom entity types! This tool uses both traditional NER models and GLiNER for comprehensive entity extraction.
 
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- ### How to use:
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  1. **πŸ“ Enter your text** in the text area below
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- 2. **🎯 Select a model** from the dropdown for common entities
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- 3. **β˜‘οΈ Select common entities** you want to find (PER, ORG, LOC, etc.)
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- 4. **✨ Add custom entities** (comma-separated) like "relationships, occupations, skills" - powered by GLiNER
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  5. **βš™οΈ Adjust confidence threshold**
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- 6. **πŸ” Click "Analyse Text"** to see results with organized output
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  (NB: common/custom entities which overlap are shown with split-colour highlighting)
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  """)
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  # Add tip box
@@ -1003,7 +1004,7 @@ def create_interface():
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  <a href="https://digitalscholarship.web.ox.ac.uk/" target="_blank" style="color: #1976d2;">
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  Digital Scholarship at Oxford (DiSc)
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  </a>
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- funded research project:
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  <em>Extracting Keywords from Crowdsourced Collections</em>.
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  </p>
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  <p style="font-size: 14px; line-height: 1.8; margin: 0;">
 
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  gr.Markdown("""
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  # Named Entity Recognition (NER) Explorer Tool
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+ Combine common Named Entity Recognition (NER) categories with your own custom entity types!
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+ This tool uses both traditional NER models and GLiNER for comprehensive entity extraction, allowing you to explore what NER looks like in practice.
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+ ### How to use this tool:
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  1. **πŸ“ Enter your text** in the text area below
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+ 2. **🎯 Select a model** from the dropdown menu
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+ 3. **β˜‘οΈ Select common entity types** you want to identify (PER, ORG, LOC, etc.)
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+ 4. **✨ Add custom entities** (comma-separated) like "relationships, occupations, skills"
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  5. **βš™οΈ Adjust confidence threshold**
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+ 6. **πŸ” Click "Analyse Text"** to see results
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  (NB: common/custom entities which overlap are shown with split-colour highlighting)
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  """)
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  # Add tip box
 
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  <a href="https://digitalscholarship.web.ox.ac.uk/" target="_blank" style="color: #1976d2;">
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  Digital Scholarship at Oxford (DiSc)
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  </a>
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+ funded research project:<br>
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  <em>Extracting Keywords from Crowdsourced Collections</em>.
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  </p>
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  <p style="font-size: 14px; line-height: 1.8; margin: 0;">