@inproceedings{eb072fad3f6247759897406f666cd639,
title = "On the evaluation of semantic phenomena in neural machine translation using natural language inference",
abstract = "We propose a process for investigating the extent to which sentence representations arising from neural machine translation (NMT) systems encode distinct semantic phenomena.We use these representations as features to train a natural language inference (NLI) classifier based on datasets recast from existing semantic annotations. In applying this process to a representative NMT system, we find its encoder appears most suited to supporting inferences at the syntax-semantics interface, as compared to anaphora resolution requiring worldknowledge. We conclude with a discussion on the merits and potential deficiencies of the existing process, and how it may be improved and extended as a broader framework for evaluating semantic coverage.",
author = "Adam Poliak and Yonatan Belinkov and James Glass and {Van Durme}, Benjamin",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics.; 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 ; Conference date: 01-06-2018 Through 06-06-2018",
year = "2018",
language = "الإنجليزيّة",
series = "NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference",
pages = "513--523",
booktitle = "Short Papers",
}