Natural Language Semantics

Results: 979



#Item
1Stone-Dual Semantics for Natural Language Introduction Mainstream possible-worlds semantics (PWS) follows Montagueand Kripkein treating the set W of worlds as unstructured and the set P of propositions (m

Stone-Dual Semantics for Natural Language Introduction Mainstream possible-worlds semantics (PWS) follows Montagueand Kripkein treating the set W of worlds as unstructured and the set P of propositions (m

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Source URL: semantique.free.fr

Language: English - Date: 2007-10-05 06:13:42
    2Inferential Role Semantics for Natural Language Peter Blouw () Chris Eliasmith () Centre for Theoretical Neuroscience, University of Waterloo Waterloo, ON, Canada N2L 3G1 Abstrac

    Inferential Role Semantics for Natural Language Peter Blouw () Chris Eliasmith () Centre for Theoretical Neuroscience, University of Waterloo Waterloo, ON, Canada N2L 3G1 Abstrac

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    Source URL: mindmodeling.org

    Language: English - Date: 2017-07-13 22:42:20
      3Semantics in generative grammar. By Irene Heim & Angelika Kratzer. Malden & Oxford: Blackwell, 1998. Pp. ix, 324. Introduction to natural language semantics. By Henriëtte de Swart. Stanford: CSLI Publications, 1998. Pp.

      Semantics in generative grammar. By Irene Heim & Angelika Kratzer. Malden & Oxford: Blackwell, 1998. Pp. ix, 324. Introduction to natural language semantics. By Henriëtte de Swart. Stanford: CSLI Publications, 1998. Pp.

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      Source URL: ncs.ruhosting.nl

      Language: English - Date: 2008-10-08 07:37:16
        4Natural Language Semantics manuscript No. (will be inserted by the editor) Non-monotonicity in NPI licensing Luka Crniˇ c

        Natural Language Semantics manuscript No. (will be inserted by the editor) Non-monotonicity in NPI licensing Luka Crniˇ c

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        Source URL: lukacrnic.com

        Language: English - Date: 2017-11-14 02:27:32
          5The child in semantics* Valentine Hacquard University of Maryland Abstract This paper discusses the challenges that children face in acquiring natural language meaning, and the kinds of linguistic and nonlinguistic capac

          The child in semantics* Valentine Hacquard University of Maryland Abstract This paper discusses the challenges that children face in acquiring natural language meaning, and the kinds of linguistic and nonlinguistic capac

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          Source URL: ling.umd.edu

          Language: English - Date: 2018-03-13 21:26:59
            6Natural Language Semantics:383–410 DOIs11050  SpringerBART GEURTS

            Natural Language Semantics:383–410 DOIs11050  SpringerBART GEURTS

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            Source URL: ncs.ruhosting.nl

            Language: English - Date: 2008-10-08 07:37:02
              7Using Frame Semantics in Natural Language Processing Apoorv Agarwal Dept. of Computer Science Columbia University New York, NY

              Using Frame Semantics in Natural Language Processing Apoorv Agarwal Dept. of Computer Science Columbia University New York, NY

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              Source URL: anthology.aclweb.org

              - Date: 2014-06-16 05:53:45
                8Semi-Supervised and Latent-Variable Models of Natural Language Semantics Dipanjan Das CMU-LTI

                Semi-Supervised and Latent-Variable Models of Natural Language Semantics Dipanjan Das CMU-LTI

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                Source URL: www.dipanjandas.com

                - Date: 2012-05-31 11:09:13
                  9Automatic adaptation of Proper Noun Dictionaries through cooperation of machine learning and probabilistic methods Georgios Petasis, Alessandro Cucchiarelli(*),Paola Velardi(§), Georgios Paliouras, Vangelis Karkaletsis,

                  Automatic adaptation of Proper Noun Dictionaries through cooperation of machine learning and probabilistic methods Georgios Petasis, Alessandro Cucchiarelli(*),Paola Velardi(§), Georgios Paliouras, Vangelis Karkaletsis,

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                  Source URL: wwwusers.di.uniroma1.it

                  Language: English - Date: 2003-01-22 10:22:20
                  10Structured Generative Models for Unsupervised Named-Entity Clustering Micha Elsner, Eugene Charniak and Mark Johnson Brown Laboratory for Linguistic Information Processing (BLLIP) Brown University Providence, RI 02912 {m

                  Structured Generative Models for Unsupervised Named-Entity Clustering Micha Elsner, Eugene Charniak and Mark Johnson Brown Laboratory for Linguistic Information Processing (BLLIP) Brown University Providence, RI 02912 {m

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                  Source URL: bllip.cs.brown.edu

                  Language: English - Date: 2009-03-29 14:56:08