ppsingh commited on
Commit
e0984c6
1 Parent(s): 6118d20
Files changed (2) hide show
  1. app.py +6 -0
  2. appStore/target.py +5 -3
app.py CHANGED
@@ -41,6 +41,12 @@ with st.expander("ℹ️ - About this app", expanded=False):
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  - Step 3: The paragraphs which are detected containing some target \
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  related information are then fed to multiple classifier to enrich the
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  Information Extraction.
 
 
 
 
 
 
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  """)
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  st.write("")
 
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  - Step 3: The paragraphs which are detected containing some target \
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  related information are then fed to multiple classifier to enrich the
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  Information Extraction.
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+ Classifers:
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+ - **Netzero**: Detects if any Netzero commitment is prresent in paragraph or not.
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+ - **GHG**: Detects if any GHG related information present in paragraph or not.
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+ - **Sector**: Detects which sectors are spoken/dsicussed about in paragraph.
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+ - **Adaptation-Mitigation**: Detects if the pragraph is related to Adaptation and/or Mitigation.
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+
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  """)
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  st.write("")
appStore/target.py CHANGED
@@ -119,19 +119,21 @@ def target_display():
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  with c2:
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  st.write('**GHG Related Paragraphs**: `{}`'.format(count_ghg))
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  st.write('**Economy-wide Related Paragraphs**: `{}`'.format(count_economy))
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-
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  hits = hits.sort_values(by=['Relevancy'], ascending=False)
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  netzerohit = hits[hits['Netzero Label'] == 'NETZERO']
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  if not netzerohit.empty:
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  netzerohit = netzerohit.sort_values(by = ['Netzero Score'], ascending = False)
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- st.markdown("###### Netzero paragraph ######")
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- st.write('** Text `page {}`: {}'.format(netzerohit.iloc[0]['page'],
 
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  netzerohit.iloc[0]['text'].replace("\n", " ")))
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  st.write("")
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  else:
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  st.info("🤔 No Netzero paragraph found")
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  # st.write("**Result {}** `page {}` (Relevancy Score: {:.2f})'".format(i+1,hits.iloc[i]['page'],hits.iloc[i]['Relevancy'])")
 
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  st.markdown("###### Top few Target Classified paragraph/text results ######")
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  range_val = min(5,len(hits))
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  for i in range(range_val):
 
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  with c2:
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  st.write('**GHG Related Paragraphs**: `{}`'.format(count_ghg))
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  st.write('**Economy-wide Related Paragraphs**: `{}`'.format(count_economy))
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+ st.write('-------------------')
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  hits = hits.sort_values(by=['Relevancy'], ascending=False)
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  netzerohit = hits[hits['Netzero Label'] == 'NETZERO']
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  if not netzerohit.empty:
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  netzerohit = netzerohit.sort_values(by = ['Netzero Score'], ascending = False)
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+ # st.write('-------------------')
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+ # st.markdown("###### Netzero paragraph ######")
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+ st.write('** Netzero paragraph `page {}`: {}'.format(netzerohit.iloc[0]['page'],
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  netzerohit.iloc[0]['text'].replace("\n", " ")))
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  st.write("")
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  else:
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  st.info("🤔 No Netzero paragraph found")
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  # st.write("**Result {}** `page {}` (Relevancy Score: {:.2f})'".format(i+1,hits.iloc[i]['page'],hits.iloc[i]['Relevancy'])")
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+ st.write('-------------------')
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  st.markdown("###### Top few Target Classified paragraph/text results ######")
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  range_val = min(5,len(hits))
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  for i in range(range_val):