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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...8 Hits 1 – 20 of 157 1 From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains ... Mather, Brodie; Dorr, Bonnie J; Dalton, Adam. - : arXiv, 2022 BASE Show details 2 Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge ... Dorr, Bonnie J.; Bhatia, Archna; Dalton, Adam. - : arXiv, 2020 BASE Show details 3 Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation ... Bhatia, Archna; Dalton, Adam; Mather, Brodie. - : arXiv, 2020 BASE Show details 4 Statistical modality tagging from rule-based annotations and crowdsourcing ... Prabhakaran, Vinodkumar; Bloodgood, Michael; Diab, Mona. - : arXiv, 2015 BASE Show details 5 Use of Modality and Negation in Semantically-Informed Syntactic MT ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2015 BASE Show details 6 A Modality Lexicon and its use in Automatic Tagging ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2014 BASE Show details 7 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ... Baker, Kathryn; Bloodgood, Michael; Callison-Burch, Chris. - : arXiv, 2014 BASE Show details 8 Computing Lexical Contrast ... Mohammad, Saif M.; Dorr, Bonnie J.; Hirst, Graeme. - : arXiv, 2013 BASE Show details 9 Use of Modality and Negation in Semantically-Informed Syntactic MT Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J... In: DTIC (2012) BASE Show details 10 Statistical Modality Tagging from Rule-based Annotations and Crowdsourcing Prabhakaran, Vinodkumar; Bloodgood, Michael; Diab, Mona. - : Association for Computational Linguistics, 2012 BASE Show details 11 Use of Modality and Negation in Semantically-Informed Syntactic MT Bloodgood, Michael; Filardo, Nathaniel; Levin, Lori. - : MIT Press, 2012 BASE Show details 12 Citation Handling: Processing Citation Texts in Scientific Documents Whidby, Michael Alan. - 2012 BASE Show details 13 Measuring Degrees of Semantic Opposition ... Mohammad, Saif M.; Dorr, Bonnie J.; Hirst, Graeme. - : National Research Council Canada, 2011 BASE Show details 14 Citation Handling for Improved Summarization of Scientific Documents Whidby, Michael; Zajic, David; Dorr, Bonnie. - 2011 BASE Show details 15 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 16 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 17 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 18 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 19 The Circle of Meaning: From Translation to Paraphrasing and Back Madnani, Nitin. - 2010 BASE Show details 20 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach Baker, Kathryn; Piatko, Christine; Miller, Scott; Callison-Burch, Chris; Bloodgood, Michael; Filardo, Nathaniel; Levin, Lori; Dorr, Bonnie. - 2010 Abstract: We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic tags assigned to the target-language training texts improved translation quality. The resulting system significantly outperformed a linguistically naive baseline model (Hiero), and reached the highest scores yet reported on the NIST 2009 Urdu-English translation task. This finding supports the hypothesis (posed by many researchers in the MT community, e.g., in DARPA GALE) that both syntactic and semantic information are critical for improving translation quality—and further demonstrates that large gains can be achieved for low-resource languages with different word order than English. ; We thank Basis Technology Corporation for their generous contribution of software components to this work. This work is supported, in part, by the Johns Hopkins Human Language Technology Center of Excellence, by the National Science Foundation under grant IIS-0713448, and by BBN Technologies under GALE DARPA/IPTO Contract No. HR0011-06-C-0022. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsor. Keyword: artificial intelligence; computational linguistics; computer science; human language technology; machine learning; machine translation; modality; named entities; natural language processing; negation; semantically-informed machine translation; semantically-informed syntactic machine translation; statistical machine translation; statistical methods; translation technology; tree-grafting; Urdu-English translation URL: https://doi.org/10.13016/M2H59F http://hdl.handle.net/1903/15579 BASE Hide details Page: 1 2 3 4 5...8

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