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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 Hits 1 – 20 of 97 1 Statistical modality tagging from rule-based annotations and crowdsourcing ... Prabhakaran, Vinodkumar; Bloodgood, Michael; Diab, Mona. - : arXiv, 2015 BASE Show details 2 Use of Modality and Negation in Semantically-Informed Syntactic MT ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2015 BASE Show details 3 A Modality Lexicon and its use in Automatic Tagging ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2014 BASE Show details 4 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ... Baker, Kathryn; Bloodgood, Michael; Callison-Burch, Chris. - : arXiv, 2014 BASE Show details 5 Computing Lexical Contrast ... Mohammad, Saif M.; Dorr, Bonnie J.; Hirst, Graeme; Turney, Peter D.. - : arXiv, 2013 Abstract: Knowing the degree of semantic contrast between words has widespread application in natural language processing, including machine translation, information retrieval, and dialogue systems. Manually-created lexicons focus on opposites, such as {\rm hot} and {\rm cold}. Opposites are of many kinds such as antipodals, complementaries, and gradable. However, existing lexicons often do not classify opposites into the different kinds. They also do not explicitly list word pairs that are not opposites but yet have some degree of contrast in meaning, such as {\rm warm} and {\rm cold} or {\rm tropical} and {\rm freezing}. We propose an automatic method to identify contrasting word pairs that is based on the hypothesis that if a pair of words, $A$ and $B$, are contrasting, then there is a pair of opposites, $C$ and $D$, such that $A$ and $C$ are strongly related and $B$ and $D$ are strongly related. (For example, there exists the pair of opposites {\rm hot} and {\rm cold} such that {\rm tropical} is related to {\rm ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1308.6300 https://dx.doi.org/10.48550/arxiv.1308.6300 BASE Hide details 6 Use of Modality and Negation in Semantically-Informed Syntactic MT Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J... In: DTIC (2012) BASE Show details 7 Statistical Modality Tagging from Rule-based Annotations and Crowdsourcing Prabhakaran, Vinodkumar; Bloodgood, Michael; Diab, Mona. - : Association for Computational Linguistics, 2012 BASE Show details 8 Use of Modality and Negation in Semantically-Informed Syntactic MT Bloodgood, Michael; Filardo, Nathaniel; Levin, Lori. - : MIT Press, 2012 BASE Show details 9 Interlingual annotation of parallel text corpora: a new framework for annotation and evaluation Siddharthan, Advaith; Habash, Nizar; Passonneau, Rebecca J.... In: Natural language engineering. - Cambridge : Cambridge University Press 16 (2010) 3, 197-243 BLLDB OLC Linguistik Show details 10 TER-Plus: paraphrase, semantic, and alignment enhancements to translation edit rate Schwartz, Richard; Snover, Matthew G.; Dorr, Bonnie Jean... In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 23 (2010) 2-3, 117-127 BLLDB OLC Linguistik Show details 11 Symbolic-to-statistical hybridization: extending generation-heavy machine translation Dorr, Bonnie Jean; Monz, Christof; Habash, Nizar In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 23 (2010) 1, 23-63 BLLDB OLC Linguistik Show details 12 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ... Baker, Kathryn; Bloodgood, Michael; Callison-Burch, Chris. - : Digital Repository at the University of Maryland, 2010 BASE Show details 13 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach Baker, Kathryn; Piatko, Christine; Miller, Scott. - 2010 BASE Show details 14 A Modality Lexicon and its use in Automatic Tagging Dorr, Bonnie; Bloodgood, Michael; Filardo, Nathaniel. - : European Language Resources Association, 2010 BASE Show details 15 A cost-effective lexical acquisition process for large-scale thesaurus translation Lin, Jimmy; Murray, G. Craig; Dorr, Bonnie Jean... In: Language resources and evaluation. - Dordrecht [u.a.] : Springer 43 (2009) 1, 27-40 BLLDB Show details 16 Language Understanding Annotation Corpus Diab, Mona; Dorr, Bonnie; Levin, Lori. - : Linguistic Data Consortium, 2009. : https://www.ldc.upenn.edu, 2009 BASE Show details 17 Language Understanding Annotation Corpus ... Diab, Mona; Dorr, Bonnie; Levin, Lori. - : Linguistic Data Consortium, 2009 BASE Show details 18 The ACL Anthology Reference Corpus: A Reference Dataset for Bibliographic Research in Computational Linguistics Bird, Steven; Dale, Robert; Dorr, Bonnie J. - : Paris : European Language Resources Association (ELRA), 2008 BASE Show details 19 Challenges in Building an Arabic-English GHMT System with SMT Components ... Habash, Nizar Y.; Dorr, Bonnie; Monz, Christof. - : Columbia University, 2006 BASE Show details 20 Text Summarization Evaluation: Correlating Human Performance on an Extrinsic Task with Automatic Intrinsic Metrics President, Stacy F.; Dorr, Bonnie J. In: DTIC (2006) BASE Show details Page: 1 2 3 4 5

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