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2-qa-earnings-sentencewise
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Upload 17 files (#13)

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- Upload 17 files (9cc881e2db3d2b5e3d904c275326b2099ac6a29d)

Files changed (2) hide show
  1. app.py +1 -0
  2. utils/entity_extraction.py +2 -2
app.py CHANGED
@@ -62,6 +62,7 @@ from utils.vector_index import (
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  create_sparse_embeddings,
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  hybrid_score_norm,
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  )
 
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  st.title("Question Answering on Earnings Call Transcripts")
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  create_sparse_embeddings,
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  hybrid_score_norm,
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  )
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+ from utils import nltkmodules
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  st.title("Question Answering on Earnings Call Transcripts")
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utils/entity_extraction.py CHANGED
@@ -1,8 +1,8 @@
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  import re
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- import nltkmodules
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  from nltk.stem import PorterStemmer, WordNetLemmatizer
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- # Keyword Extracttion
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  def expand_list_of_lists(list_of_lists):
 
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  import re
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+
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  from nltk.stem import PorterStemmer, WordNetLemmatizer
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+ # Keyword Extraction
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  def expand_list_of_lists(list_of_lists):