263 research outputs found

    Three Algorithms for Competence-Oriented Anaphor Resolution

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    In the last decade, much effort went into the design of robust third-person pronominal anaphor resolution algorithms. Typical approaches are reported to achieve an accuracy of 60-85%. Recent research addresses the question of how to deal with the remaining difficult-toresolve anaphors. Lappin (2004) proposes a sequenced model of anaphor resolution according to which a cascade of processing modules employing knowledge and inferencing techniques of increasing complexity should be applied. The individual modules should only deal with and, hence, recognize the subset of anaphors for which they are competent. It will be shown that the problem of focusing on the competence cases is equivalent to the problem of giving precision precedence over recall. Three systems for high precision robust knowledge-poor anaphor resolution will be designed and compared: a ruleset-based approach, a salience threshold approach, and a machine-learning-based approach. According to corpus-based evaluation, there is no unique best approach. Which approach scores highest depends upon type of pronominal anaphor as well as upon text genre

    Using \u27Low-cost\u27 Learning Features for Pronoun Resolution

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    PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

    Using Zero Anaphora Resolution to Improve Text Categorization

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    Anaphora Resolution and Text Retrieval

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    Empirical approaches based on qualitative or quantitative methods of corpus linguistics have become a central paradigm within linguistics. The series takes account of this fact and provides a platform for approaches within synchronous linguistics as well as interdisciplinary works with a linguistic focus which devise new ways of working empirically and develop new data-based methods and theoretical models for empirical linguistic analyses

    Coreference-Based Summarization and Question Answering: a Case for High Precision Anaphor Resolution

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    Approaches to Text Summarization and Question Answering are known to benefit from the availability of coreference information. Based on an analysis of its contributions, a more detailed look at coreference processing for these applications will be proposed: it should be considered as a task of anaphor resolution rather than coreference resolution. It will be further argued that high precision approaches to anaphor resolution optimally match the specific requirements. Three such approaches will be described and empirically evaluated, and the implications for Text Summarization and Question Answering will be discussed

    Anaphors in Sanskrit

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    Proceedings of the Second Workshop on Anaphora Resolution (WAR II). Editor: Christer Johansson. NEALT Proceedings Series, Vol. 2 (2008), 11-25. © 2008 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/7129

    Anaphora Resolution and Text Retrieval

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    Empirical approaches based on qualitative or quantitative methods of corpus linguistics have become a central paradigm within linguistics. The series takes account of this fact and provides a platform for approaches within synchronous linguistics as well as interdisciplinary works with a linguistic focus which devise new ways of working empirically and develop new data-based methods and theoretical models for empirical linguistic analyses

    About adequacy, equivalence and translatability in human and machine translation

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    This paper examines the concepts of adequacy, equivalence and translatability in human translation and how in particular the concept of adequacy evolves with respect to the evaluation of the quality in Machine Translation. The paper starts with the analysis of the notions of translated sense and adequacy as discussed in translation theory and highlights how the considerations on the nature of human translation lose their theoretical strength if applied to Machine translation (MT). The different ways of conceiving the sense in human and machine translation with regard to the concepts of adequacy and equivalence, lead to different interpretations of the relationship between source and target text
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