Dependency-based paraphrasing for recognizing textual entailment

E.C. Marsi, E.J. Krahmer, W.E. Bosma

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    Abstract

    In this article we address the usefulness of linguistic-independent methods in extractive Automatic Summarization, arguing that linguistic knowledge is not only useful, but may be necessary to improve the informativeness of automatic extracts. An assessment of four diverse AS methods on Brazilian Portuguese texts is presented to support our claim. One of them is Mihalcea’s TextRank; other two are modified versions of the former through the inclusion of varied linguistic features. Finally, the fourth method employs machine learning techniques, tackling more profound and language-dependent knowledge.
    Original languageUndefined
    Title of host publicationProceedings of ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
    Place of PublicationEast Stroudsburg, PA, USA
    PublisherAssociation for Computational Linguistics (ACL)
    Pages83-88
    Number of pages6
    ISBN (Print)not assigned
    Publication statusPublished - Jun 2007

    Publication series

    Name
    PublisherAssociation for Computational Linguistics
    NumberSupplement

    Keywords

    • IR-64526
    • METIS-245855
    • EWI-11548

    Cite this

    Marsi, E. C., Krahmer, E. J., & Bosma, W. E. (2007). Dependency-based paraphrasing for recognizing textual entailment. In Proceedings of ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (pp. 83-88). East Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).