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1 Parent(s): 15c3a36
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  1. app.py +4 -3
app.py CHANGED
@@ -11,15 +11,15 @@ en_nlp = stanza.Pipeline('en', processors='tokenize')
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  article='''
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- # Discourse Structure of Long-form Answers.
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  ## About
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  This is a demo for our paper: [How Do We Answer Complex Questions: Discourse Structure of Long-form Answers](https://aclanthology.org/2022.acl-long.249/).
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  Fangyuan Xu, Junyi Jessy Li, Eunsol Choi. 2022.
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- Contact: [Fangyuan Xu](https://www.cs.utexas.edu/~fxu/) via firstname@utexas.edu
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  ## Model
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  The model served here is a T5(large)-based role classification model trained on functional roles of ELI5 answers.
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  ## Resources
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- Please see more information (paper/code/data/datasheet) at our [website](https://www.cs.utexas.edu/~fxu/lfqa_discourse/index.html)!
 
 
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  '''
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  role_mappings = {
@@ -29,6 +29,7 @@ role_mappings = {
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  'Answer - Example': 'Example',
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  'Miscellaneous': 'Miscellaneous',
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  'Answer - Organizational sentence': 'Organizational sentence',
 
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  }
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  def get_ans_sentence_with_stanza(answer_paragraph, pipeline,
 
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  article='''
 
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  ## About
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  This is a demo for our paper: [How Do We Answer Complex Questions: Discourse Structure of Long-form Answers](https://aclanthology.org/2022.acl-long.249/).
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  Fangyuan Xu, Junyi Jessy Li, Eunsol Choi. 2022.
 
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  ## Model
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  The model served here is a T5(large)-based role classification model trained on functional roles of ELI5 answers.
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  ## Resources
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+ Please see more information (paper/code/data/datasheet) at our [website](https://www.cs.utexas.edu/~fxu/lfqa_discourse/index.html).
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+ ## Contact
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+ [Fangyuan Xu](https://www.cs.utexas.edu/~fxu/) via firstname@utexas.edu
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  '''
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  role_mappings = {
 
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  'Answer - Example': 'Example',
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  'Miscellaneous': 'Miscellaneous',
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  'Answer - Organizational sentence': 'Organizational sentence',
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+ ' ': ' ',
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  }
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  def get_ans_sentence_with_stanza(answer_paragraph, pipeline,