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Adaptation of machine translation for multilingual information retrieval in the medical domain
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In: Pecina, Pavel, Dušek, Ondřej, Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Hajič, Jan, Hlaváčová, Jaroslava, Jones, Gareth J.F. orcid:0000-0002-4033-9135 , Kelly, Liadh orcid:0000-0003-1131-5238 , Leveling, Johannes orcid:0000-0003-0603-4191 , Mareček, David, Novák, Michal, Popel, Martin, Rosa, Rudolf, Tamchyna, Aleš and Urešová, Zdeňka (2014) Adaptation of machine translation for multilingual information retrieval in the medical domain. Artificial Intelligence in Medicine, 61 (3). pp. 165-185. ISSN 1873-2860 (2014)
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Adaptation of machine translation for multilingual information retrieval in the medical domain
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In: ISSN: 0933-3657 ; Artificial Intelligence in Medicine ; https://hal.archives-ouvertes.fr/hal-01921881 ; Artificial Intelligence in Medicine, Elsevier, 2014, 61 (3), pp.165 - 185. ⟨10.1016/j.artmed.2014.01.004⟩ (2014)
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HamleDT 2.0
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Zeman, Daniel; Mareček, David; Mašek, Jan; Popel, Martin; Ramasamy, Loganathan; Rosa, Rudolf; Štěpánek, Jan; Žabokrtský, Zdeněk. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2014
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Abstract:
HamleDT 2.0 is a collection of 30 existing treebanks harmonized into a common annotation style, the Prague Dependencies, and further transformed into Stanford Dependencies, a treebank annotation style that became popular recently. We use the newest basic Universal Stanford Dependencies, without added language-specific subtypes.
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Keyword:
common annotation style; harmonization; Interset; Prague dependencies; Stanford dependencies; treebank
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URL: http://hdl.handle.net/11858/00-097C-0000-0023-9551-4
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