Summary of the paper

Title A Corpus of Word-Aligned Asked and Anticipated Questions in a Virtual Patient Dialogue System
Authors Ajda Gokcen, Evan Jaffe, Johnsey Erdmann, Michael White and Douglas Danforth
Abstract We present a corpus of virtual patient dialogues to which we have added manually annotated gold standard word alignments. Since each question asked by a medical student in the dialogues is mapped to a canonical, anticipated version of the question, the corpus implicitly defines a large set of paraphrase (and non-paraphrase) pairs. We also present a novel process for selecting the most useful data to annotate with word alignments and for ensuring consistent paraphrase status decisions. In support of this process, we have enhanced the earlier Edinburgh alignment tool (Cohn et al., 2008) and revised and extended the Edinburgh guidelines, in particular adding guidance intended to ensure that the word alignments are consistent with the overall paraphrase status decision. The finished corpus and the enhanced alignment tool are made freely available.
Topics Corpus (Creation, Annotation, etc.), Dialogue, Textual Entailment and Paraphrasing
Full paper A Corpus of Word-Aligned Asked and Anticipated Questions in a Virtual Patient Dialogue System
Bibtex @InProceedings{GOKCEN16.679,
  author = {Ajda Gokcen and Evan Jaffe and Johnsey Erdmann and Michael White and Douglas Danforth},
  title = {A Corpus of Word-Aligned Asked and Anticipated Questions in a Virtual Patient Dialogue System},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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