Ranking paragraphs foriImproving answer recall in open-domain Question Answering

Jinhyuk Lee, Seongjun Yun, Hyunjae Kim, Miyoung Ko, Jaewoo Kang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    16 Citations (Scopus)

    Abstract

    Recently, open-domain question answering (QA) has been combined with machine comprehension models to find answers in a large knowledge source. As open-domain QA requires retrieving relevant documents from text corpora to answer questions, its performance largely depends on the performance of document retrievers. However, since traditional information retrieval systems are not effective in obtaining documents with a high probability of containing answers, they lower the performance of QA systems. Simply extracting more documents increases the number of irrelevant documents, which also degrades the performance of QA systems. In this paper, we introduce Paragraph Ranker which ranks paragraphs of retrieved documents for a higher answer recall with less noise. We show that ranking paragraphs and aggregating answers using Paragraph Ranker improves performance of open-domain QA pipeline on the four open-domain QA datasets by 7.8% on average.

    Original languageEnglish
    Title of host publicationProceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
    EditorsEllen Riloff, David Chiang, Julia Hockenmaier, Jun'ichi Tsujii
    PublisherAssociation for Computational Linguistics
    Pages565-569
    Number of pages5
    ISBN (Electronic)9781948087841
    Publication statusPublished - 2020 Jan 1
    Event2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 - Brussels, Belgium
    Duration: 2018 Oct 312018 Nov 4

    Publication series

    NameProceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

    Conference

    Conference2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
    Country/TerritoryBelgium
    CityBrussels
    Period18/10/3118/11/4

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Computer Science Applications
    • Information Systems

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