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IJCNLP-2017 Task 4: Customer Feedback Analysis.

, , , and . IJCNLP (Shared Tasks), page 26-33. Asian Federation of Natural Language Processing, (2017)

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A Syntactic Skeleton for Statistical Machine Translation., , , , and . EAMT, European Association for Machine Translation, (2006)Example-Based Machine Translation of the Basque Language., , , and . AMTA, page 232-241. Association for Machine Translation in the Americas, (2006)Robust Sub-Sentential Alignment of Phrase-Structure Trees., , and . COLING, (2004)Leveraging Pre-trained Language Models for Gender Debiasing., , , and . LREC, page 2188-2195. European Language Resources Association, (2022)Meta-Evaluation of a Diagnostic Quality Metric for Machine Translation., , , and . MTSummit, (2013)Hybrid data-driven models of machine translation., and . Mach. Transl., 19 (3-4): 301-323 (2005)Contextual Bitext-Derived Paraphrases in Automatic MT Evaluation., , , and . WMT@HLT-NAACL, page 86-93. Association for Computational Linguistics, (2006)Dublin City University at CLEF 2004: Experiments with the ImageCLEF St Andrew's Collection., , , , , and . CLEF (Working Notes), volume 1170 of CEUR Workshop Proceedings, CEUR-WS.org, (2004)MTWatch: A Tool for the Analysis of Noisy Parallel Data., and . LREC, page 41-45. European Language Resources Association (ELRA), (2014)OpenMaTrEx: A Free/Open-Source Marker-Driven Example-Based Machine Translation System., , , , , and . IceTAL, volume 6233 of Lecture Notes in Computer Science, page 121-126. Springer, (2010)