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APE-QUEST: an MT Quality Gate., , , and . EAMT, page 473-474. European Association for Machine Translation, (2020)Collecting domain specific data for MT: an evaluation of the ParaCrawlpipeline., , , , , , , and . MTSummit (2), page 186-195. European Association for Machine Translation, (2019)APE-QUEST., , , , , , , , , and 2 other author(s). MTSummit (2), page 110-111. European Association for Machine Translation, (2019)Misalignment Detection for Web-Scraped Corpora: A Supervised Regression Approach., , , , , , , , , and . Informatics, 6 (3): 35 (2019)ELRC Action: Covering Confidentiality, Correctness and Cross-linguality., , , , , and . LREC, page 6240-6249. European Language Resources Association, (2022)Automatically extracting the semantic network out of public services to support cities becoming Smart Cities., , , , , , , , and . EAMT, page 341-342. European Association for Machine Translation, (2022)CEFAT4Cities, a Natural Language Layer for the ISA2 Core Public Service Vocabulary., , , , , , , and . EAMT, page 483-484. European Association for Machine Translation, (2020)Being Generous with Sub-Words towards Small NMT Children., , , , and . LREC, page 3650-3656. European Language Resources Association, (2020)A Post-Editing Dataset in the Legal Domain: Do we Underestimate Neural Machine Translation Quality?, , , , , , , , and . LREC, page 3692-3697. European Language Resources Association, (2020)