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Computer Science > Computation and Language

arXiv:1805.05942 (cs)
[Submitted on 15 May 2018]

Title:Harvesting Paragraph-Level Question-Answer Pairs from Wikipedia

Authors:Xinya Du, Claire Cardie
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Abstract:We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence. We propose a neural network approach that incorporates coreference knowledge via a novel gating mechanism. Compared to models that only take into account sentence-level information (Heilman and Smith, 2010; Du et al., 2017; Zhou et al., 2017), we find that the linguistic knowledge introduced by the coreference representation aids question generation significantly, producing models that outperform the current state-of-the-art. We apply our system (composed of an answer span extraction system and the passage-level QG system) to the 10,000 top-ranking Wikipedia articles and create a corpus of over one million question-answer pairs. We also provide a qualitative analysis for this large-scale generated corpus from Wikipedia.
Comments: Accepted to ACL 2018 (long paper)
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:1805.05942 [cs.CL]
  (or arXiv:1805.05942v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.1805.05942

Submission history

From: Xinya Du [view email]
[v1] Tue, 15 May 2018 17:58:25 UTC (433 KB)
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