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    ACL
    2009
    109views Computational Linguistics» more  ACL 2009»
    Using Syntax to Disambiguate Explicit Discourse Connectives in Text
    13 years 7 months ago
    Using Syntax to Disambiguate Explicit Discourse Connectives in Text
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    Discourse connectives are words or phrases such as once, since, and on the contrary that explicitly signal the presence of a discourse relation. There are two types of ambiguity t...
    Emily Pitler, Ani Nenkova
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    ACL
    2009
    150views Computational Linguistics» more  ACL 2009»
    Learning foci for Question Answering over Topic Maps
    13 years 7 months ago
    Learning foci for Question Answering over Topic Maps
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    This paper introduces the concepts of asking point and expected answer type as variations of the question focus. They are of particular importance for QA over semistructured data,...
    Alexander Mikhailian, Tiphaine Dalmas, Rani Pinchu...
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    ACL
    2009
    160views Computational Linguistics» more  ACL 2009»
    Active Learning for Multilingual Statistical Machine Translation
    13 years 7 months ago
    Active Learning for Multilingual Statistical Machine Translation
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    Statistical machine translation (SMT) models require bilingual corpora for training, and these corpora are often multilingual with parallel text in multiple languages simultaneous...
    Gholamreza Haffari, Anoop Sarkar
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    ACL
    2009
    147views Computational Linguistics» more  ACL 2009»
    Co-Training for Cross-Lingual Sentiment Classification
    13 years 7 months ago
    Co-Training for Cross-Lingual Sentiment Classification
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    The lack of Chinese sentiment corpora limits the research progress on Chinese sentiment classification. However, there are many freely available English sentiment corpora on the W...
    Xiaojun Wan
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    ACL
    2009
    130views Computational Linguistics» more  ACL 2009»
    Unsupervised Learning of Narrative Schemas and their Participants
    13 years 7 months ago
    Unsupervised Learning of Narrative Schemas and their Participants
    Download  cs.stanford.edu
    We describe an unsupervised system for learning narrative schemas, coherent sequences or sets of events (arrested(POLICE,SUSPECT), convicted( JUDGE, SUSPECT)) whose arguments are ...
    Nathanael Chambers, Dan Jurafsky
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