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Topic-informed neural machine translation
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In: Zhang, Jian, Li, Liangyou orcid:0000-0002-0279-003X , Way, Andy orcid:0000-0001-5736-5930 and Liu, Qun orcid:0000-0002-7000-1792 (2016) Topic-informed neural machine translation. In: 26th International Conference on Computational Linguistics, 13-16 Dec 2016, Osaka, Japan. (2016)
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Is all that glitters in MT quality estimation really gold standard?
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In: Graham, Yvette, Baldwin, Timothy, Dowling, Meghan orcid:0000-0003-1637-4923 , Eskevich, Maria, Lynn, Teresa and Tounsi, Lamia (2016) Is all that glitters in MT quality estimation really gold standard? In: 26th International Conference on Computational Linguistics, 11-17 Dec 2016, Osaka, Japan. ISBN 978-4-87974-702-0 (2016)
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Reports of the AAAI 2011 Fall Symposia
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In: ISSN: 0738-4602 ; AI magazine ; https://hal.archives-ouvertes.fr/hal-02797990 ; AI magazine, Association for the Advancement of Artificial Intelligence, 2012, 33 (1), pp.71-78. ⟨10.1609/aimag.v33i1.2391⟩ (2012)
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Using Entity Features to Classify Implicit Discourse Relations
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In: Departmental Papers (CIS) (2010)
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The Penn Discourse Treebank 2.0 Annotation Manual
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In: IRCS Technical Reports Series (2007)
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Constraints on the *generation of referring expressions, with special reference to Hindi
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In: Dissertations available from ProQuest (2003)
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Abstract:
This dissertation makes a progress towards the generation of referring expressions in Hindi. We first make a proposal to exploit a combination of Gricean implicatures (Grice, 1975) and Centering theory constraints (Grosz et al., 1995) to formulate a generation algorithm for referring expressions whose domain of application is defined in terms of the Centering Transitions. The formulated algorithm is an abstraction over the cross-linguistic variability observed across languages. To set the language-specific parameters of the algorithm, in particular the parameter that decides the relative salience of the discourse entities in an utterance, we propose a corpus-based methodology to identify the ways in which discourse salience is realized linguistically in any language. We apply this method to a Hindi corpus to investigate three possible linguistic reflexes of discourse salience: grammatical role, word order, and information status, and show that Hindi does not display exhibit any correlation between discourse salience and either word order or information status, and that grammatical function emerges as the primary determinant of salience. Using the results of the proposed methodology for Hindi, we provide an analysis of Hindi zero pronouns. We argue that the constraints on the use of zeros in Hindi are neither syntactic (Kameyama, 1985) nor explicable purely in terms of the singular notion of the topic (Butt & King, 1997). Our analysis, provided in terms of Centering transition preferences, shows that pronouns can be dropped in Hindi only when they occur in an utterance following a CONTINUE or a SMOOTH-SHIFT transition, thus demonstrating the importance of the Preferred Center for zero pronoun realization. Finally, with respect to the problem of defining the utterance unit for discourse, we provide an analysis of complex sentences containing relative clauses. We argue that different kinds of relative clauses have different utterance statuses as well as different effects on the hierarchical organization of discourse segments. Non-restrictive relative clauses form a distinct but embedded utterance unit, while restrictives are part of the main clause unit. Our data also provide support for partitioning the class of restrictive relatives into indefinite head and definite head restrictives (Prince, 1990), with indefinite head restrictives patterning like non-restrictives.
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Keyword:
Linguistics|Computer science
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URL: https://repository.upenn.edu/dissertations/AAI3087452
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