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  • 标题:Discrete Reasoning Templates for Natural Language Understanding
  • 本地全文:下载
  • 作者:Hadeel Al-Negheimish ; Pranava Madhyastha ; Alessandra Russo
  • 期刊名称:Conference on European Chapter of the Association for Computational Linguistics (EACL)
  • 出版年度:2021
  • 卷号:2021
  • 页码:80-87
  • DOI:10.18653/v1/2021.eacl-srw.12
  • 语种:English
  • 出版社:ACL Anthology
  • 摘要:Reasoning about information from multiple parts of a passage to derive an answer is an open challenge for reading-comprehension models. In this paper, we present an approach that reasons about complex questions by decomposing them to simpler subquestions that can take advantage of single-span extraction reading-comprehension models, and derives the final answer according to instructions in a predefined reasoning template. We focus on subtraction based arithmetic questions and evaluate our approach on a subset of the DROP dataset. We show that our approach is competitive with the state of the art while being interpretable and requires little supervision.
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