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Predicting Target Language CCG Supertags Improves Neural Machine Translation., , , , , , and . WMT, page 68-79. Association for Computational Linguistics, (2017)Modeling Selectional Preferences of Verbs and Nouns in String-to-Tree Machine Translation., , and . WMT, page 32-42. The Association for Computer Linguistics, (2016)Edinburgh's Syntax-Based Machine Translation Systems., , and . WMT@ACL, page 170-176. The Association for Computer Linguistics, (2013)Edinburgh's Syntax-Based Systems at WMT 2015., , , , and . WMT@EMNLP, page 199-209. The Association for Computer Linguistics, (2015)Syntax-aware Neural Machine Translation Using CCG., , , , , , and . CoRR, (2017)Edinburgh's Syntax-Based Systems at WMT 2014., , , , , and . WMT@ACL, page 207-214. The Association for Computer Linguistics, (2014)Enabling Robust Grammatical Error Correction in New Domains: Datasets, Metrics, and Analyses., , and . Trans. Assoc. Comput. Linguistics, (2019)The Feasibility of HMEANT as a Human MT Evaluation Metric., , , , , and . WMT@ACL, page 52-61. The Association for Computer Linguistics, (2013)Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1., and . W-NUT@EMNLP, page 27-33. Association for Computational Linguistics, (2019)Edinburgh's Statistical Machine Translation Systems for WMT16., , , , , and . WMT, page 399-410. The Association for Computer Linguistics, (2016)