Text-to-text generation for question answering

W.E. Bosma, Erwin Marsi, Emiel Krahmer, Mariet Theune

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    In this chapter, we describe our efforts in text-to-text generation within the IMOGEN project. In particular, we describe two focus areas of research to improve the quality of the answer: (a) graph-based content selection to improve the answer in terms of usefulness, and (b) sentence fusion to improve the answer in terms of formulation. We use sentence fusion to join together multiple sentences in order to eliminate overlapping parts, thereby reducing redundancy. The results of this work have been applied in the IMIX system. This system uses a question answering system to pinpoint fragments of text which are relevant to the information need expressed by the user. A content selection system then uses these fragments as entry points in the text to formulate a more complete answer. Sentence fusion is applied to manipulate the result in order to increase the fluency of the text.
    Original languageUndefined
    Title of host publicationInteractive Multi-modal Question-Answering
    EditorsAntal van den Bosch, Gosse Bouma
    Place of PublicationBerlin
    Number of pages29
    ISBN (Print)978-3-642-17524-4
    Publication statusPublished - 2011

    Publication series

    NameTheory and Applications of Natural Language Processing
    PublisherSpringer Verlag
    ISSN (Print)2192-032X


    • IR-78522
    • EWI-20800
    • METIS-281563

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