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1
Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction ...
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WTC1.1 (WikiTailor corpus v. 1.1) ...
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3
WTC1.0 (WikiTailor corpus v. 1.0) ...
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4
WTC1.1 (WikiTailor corpus v. 1.1) ...
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5
Pairwise Neural Machine Translation Evaluation ...
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6
Crowdsourcing and Aggregating Nested Markable Annotations
Madge, Chris; Yu, Juntao; Chamberlain, Jon. - : Association for Computational Linguistics, 2019
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7
Multilingual and cross-lingual graded lexical entailment
Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019
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8
How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019
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9
Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment
Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019
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10
Cross-Language Question Re-Ranking ...
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11
Discourse Structure in Machine Translation Evaluation ...
Abstract: In this article, we explore the potential of using sentence-level discourse structure for machine translation evaluation. We first design discourse-aware similarity measures, which use all-subtree kernels to compare discourse parse trees in accordance with the Rhetorical Structure Theory (RST). Then, we show that a simple linear combination with these measures can help improve various existing machine translation evaluation metrics regarding correlation with human judgments both at the segment- and at the system-level. This suggests that discourse information is complementary to the information used by many of the existing evaluation metrics, and thus it could be taken into account when developing richer evaluation metrics, such as the WMT-14 winning combined metric DiscoTKparty. We also provide a detailed analysis of the relevance of various discourse elements and relations from the RST parse trees for machine translation evaluation. In particular we show that: (i) all aspects of the RST tree are relevant, ... : machine translation, machine translation evaluation, discourse analysis. Computational Linguistics, 2017 ...
Keyword: 68T50; Computation and Language cs.CL; FOS Computer and information sciences; I.2.7
URL: https://dx.doi.org/10.48550/arxiv.1710.01504
https://arxiv.org/abs/1710.01504
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12
Machine Translation Evaluation with Neural Networks ...
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13
Using Word Embeddings to Enforce Document-Level Lexical Consistency in Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 85-96 (2017) (2017)
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14
High-order low-rank tensors for semantic role labeling
In: MIT Web Domain (2015)
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15
FINET: context-aware fine-grained named entity typing
Abujabal, Abdalghani; Corro, Luciano del; Gemulla, Rainer. - : Assoc. for Computational Linguistics, 2015
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16
A hybrid machine translation architecture guided by syntax
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 28 (2014) 2, 91-125
OLC Linguistik
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17
Special issue on statistical learning of natural language structured input and output
In: Natural language engineering. - Cambridge : Cambridge University Press 18 (2012) 2, 147-153
OLC Linguistik
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18
2009 CoNLL Shared Task Part 1
Hajič, Jan; Maria Antonia Martí; Marquez, Lluis. - : Linguistic Data Consortium, 2012. : https://www.ldc.upenn.edu, 2012
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19
2009 CoNLL Shared Task Part 1 ...
Maria Antonia Martí; Marquez, Lluis; Nivre, Joakim. - : Linguistic Data Consortium, 2012
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20
SemEval-2010 Task 1 OntoNotes English: Coreference Resolution in Multiple Languages
Recasens, Marta; Marquez, Lluis; Sapena, Emili. - : Linguistic Data Consortium, 2011. : https://www.ldc.upenn.edu, 2011
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