Entry Watanabe:2012:LDL from talip.bib

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BibTeX entry

@Article{Watanabe:2012:LDL,
  author =       "Yotaro Watanabe and Junta Mizuno and Eric Nichols and
                 Katsuma Narisawa and Keita Nabeshima and Naoaki Okazaki
                 and Kentaro Inui",
  title =        "Leveraging Diverse Lexical Resources for Textual
                 Entailment Recognition",
  journal =      j-TALIP,
  volume =       "11",
  number =       "4",
  pages =        "18:1--18:??",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382593.2382600",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Thu Dec 6 07:40:55 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "Since the problem of textual entailment recognition
                 requires capturing semantic relations between diverse
                 expressions of language, linguistic and world knowledge
                 play an important role. In this article, we explore the
                 effectiveness of different types of currently available
                 resources including synonyms, antonyms,
                 hypernym-hyponym relations, and lexical entailment
                 relations for the task of textual entailment
                 recognition. In order to do so, we develop an
                 entailment relation recognition system which utilizes
                 diverse linguistic analyses and resources to align the
                 linguistic units in a pair of texts and identifies
                 entailment relations based on these alignments. We use
                 the Japanese subset of the NTCIR-9 RITE-1 dataset for
                 evaluation and error analysis, conducting ablation
                 testing and evaluation on hand-crafted alignment gold
                 standard data to evaluate the contribution of
                 individual resources. Error analysis shows that
                 existing knowledge sources are effective for RTE, but
                 that their coverage is limited, especially for
                 domain-specific and other low-frequency expressions. To
                 increase alignment coverage on such expressions, we
                 propose a method of alignment inference that uses
                 syntactic and semantic dependency information to
                 identify likely alignments without relying on external
                 resources. Evaluation adding alignment inference to a
                 system using all available knowledge sources shows
                 improvements in both precision and recall of entailment
                 relation recognition.",
  acknowledgement = ack-nhfb,
  articleno =    "18",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
}

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