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The Fifth PASCAL Recognizing Textual Entailment Challenge., , , , and . TAC, NIST, (2009)Gender Bias in Machine Translation., , , , and . CoRR, (2021)Textual entailment graphs., , , and . Nat. Lang. Eng., 21 (5): 699-724 (2015)The IWSLT 2015 Evaluation Campaign., , , , , and . IWSLT (Evaluation Campaign), (2015)Extending the MuST-C Corpus for a Comparative Evaluation of Speech Translation Technology., , , , , and . EAMT, page 359-360. European Association for Machine Translation, (2022)Evaluating Cross-Language Annotation Transfer in the MultiSemCor Corpus., , and . COLING, (2004)EnetCollect in Italy., , , , , , , and . CLiC-it, volume 2253 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)Assessing the Impact of Translation Errors on Machine Translation Quality with Mixed-effects Models., , , and . EMNLP, page 1643-1653. ACL, (2014)How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation., , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 3576-3589. Association for Computational Linguistics, (2021)SICK through the SemEval glasses. Lesson learned from the evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment., , , , , and . Lang. Resour. Evaluation, 50 (1): 95-124 (2016)