QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines

@article{Pyatkin2020QADiscourseD,
  title={QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines},
  author={Valentina Pyatkin and Ayal Klein and Reut Tsarfaty and I. Dagan},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.02815}
}
  • Valentina Pyatkin, Ayal Klein, +1 author I. Dagan
  • Published 2020
  • Computer Science
  • ArXiv
  • Discourse relations describe how two propositions relate to one another, and identifying them automatically is an integral part of natural language understanding. However, annotating discourse relations typically requires expert annotators. Recently, different semantic aspects of a sentence have been represented and crowd-sourced via question-and-answer (QA) pairs. This paper proposes a novel representation of discourse relations as QA pairs, which in turn allows us to crowd-source wide… CONTINUE READING
    2 Citations
    Similarity or deeper understanding? Analyzing the TED-Q dataset of evoked questions
    The Extraordinary Failure of Complement Coercion Crowdsourcing
    • PDF

    References

    SHOWING 1-10 OF 44 REFERENCES
    Crowdsourcing Question-Answer Meaning Representations
    • 37
    • PDF
    Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task
    • 7
    • PDF
    Improving Crowdsourcing-Based Annotation of Japanese Discourse Relations
    • 2
    • PDF
    Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language
    • 111
    • Highly Influential
    • PDF
    Large-Scale QA-SRL Parsing
    • 37
    • Highly Influential
    • PDF
    TED-Q: TED Talks and the Questions they Evoke
    • 3
    • PDF