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Hits 1 – 20 of 48
1
Abstract Meaning Representation (AMR) Annotation Release 3.0
Knight, Kevin
;
Badarau, Bianca
;
Baranescu, Laura
. - : Linguistic Data Consortium, 2020. : https://www.ldc.upenn.edu, 2020
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2
Abstract Meaning Representation (AMR) Annotation Release 3.0 ...
Knight, Kevin
;
Badarau, Bianca
;
Baranescu, Laura
. - : Linguistic Data Consortium, 2020
BASE
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3
Abstract Meaning Representation (AMR) Annotation Release 2.0
Knight, Kevin
;
Badarau, Bianca
;
Baranescu, Laura
. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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4
Abstract Meaning Representation (AMR) Annotation Release 2.0 ...
Knight, Kevin
;
Badarau, Bianca
;
Baranescu, Laura
. - : Linguistic Data Consortium, 2017
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5
Abstract Meaning Representation (AMR) Annotation Release 1.0
Knight, Kevin
;
Baranescu, Laura
;
Bonial, Claire
. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
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6
HyTER Networks of Selected OpenMT08/09 Sentences
Dreyer, Markus
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
Abstract:
*Introduction* HyTER Networks of Selected OpenMT08/09 Progress Set Sentences was developed by SDL and contains HyTER (Hybrid Translation Edit Rate) networks for 102 selected source Arabic and Chinese sentences from OpenMT08 and OpenMT09 Progress Set data. HyTER is an evaluation metric based on large reference networks created by an annotation tool that allows users to develop an exponential number of correct translations for a given sentence. Reference networks can be used as a foundation for developing improved machine translation evaluation metrics and for automating the evaluation of human translation efficiency. *Data* The source material is comprised of Arabic and Chinese newswire and web data collected by LDC in 2007. Annotators created meaning-equivalent annotations under three annotation protocols. In the first protocol, foreign language native speakers built English networks starting from foreign language sentences. In the second, English native speakers built English networks from the best translation of a foreign language sentence as identified by NIST (National Institute of Standards and Technology). In the third protocol, English native speakers built English networks starting from the best translation, but those annotators also had access to three additional, independently produced human translations. Networks created by different annotators for each sentence were combined and evaluated. This release includes the source sentences and four human reference translations produced by LDC in XML format, along with five machine translation system outputs representing a variety of system architectures and performance, and the human post-edited output of those systems also presented in XML. *Samples* Please view this FST sample and Reference XML sample. *Updates* None at this time.
URL:
https://catalog.ldc.upenn.edu/LDC2014T09
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7
HyTER Networks of Selected OpenMT08/09 Sentences ...
Dreyer, Markus
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2014
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8
Abstract Meaning Representation (AMR) Annotation Release 1.0 ...
Palmer, Martha
;
Marcu, Daniel
;
Griffitt, Kira
. - : Linguistic Data Consortium, 2014
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9
Hierarchical search for word alignment
Riesa, Jason
;
Marcu, Daniel
In:
Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL
48 (2010) 1, 157-166
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10
Induction of Word and Phrase Alignments for Automatic Document Summarization ...
Daumé, Hal
;
Marcu, Daniel
. - : arXiv, 2009
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11
Measuring word alignment quality for statistical machine translation
Marcu, Daniel
;
Fraser, Alexander
In:
Computational linguistics. - Cambridge, Mass. : MIT Press
33 (2007) 3, 293-303
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12
ISI Chinese-English Automatically Extracted Parallel Text
Dragos Stefan Munteanu
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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13
ISI Arabic-English Automatically Extracted Parallel Text
Dragos Stefan Munteanu
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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14
ISI Chinese-English Automatically Extracted Parallel Text ...
Dragos Stefan Munteanu
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2007
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15
ISI Arabic-English Automatically Extracted Parallel Text ...
Dragos Stefan Munteanu
;
Marcu, Daniel
. - : Linguistic Data Consortium, 2007
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16
Scalable Inference and Training of Context-Rich Syntactic Translation Models
Graehl, Jonathan
;
Galley, Michel
;
DeNeefe, Steve
. - : Proceedings of COLING/ACL, 2006
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17
Scalable Inference and Training of Context-Rich Syntactic Translation Models ...
Galley, Michel
;
Graehl, Jonathan
;
Knight, Kevin
. - : Columbia University, 2006
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18
Improving machine translation performance by exploiting non-parallel corpora
Munteanu, Dragos Stefan
;
Marcu, Daniel
In:
Computational linguistics. - Cambridge, Mass. : MIT Press
31 (2005) 4, 477-504
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OLC Linguistik
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19
Induction of word and phrase alignments for automatic document summarization
Daumé, Hal
;
Marcu, Daniel
In:
Computational linguistics. - Cambridge, Mass. : MIT Press
31 (2005) 4, 505-530
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OLC Linguistik
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20
What's in a Translation Rule
Galley, Michel
;
Hopkins, Mark
;
Knight, Kevin
...
In: DTIC (2004)
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