Abstract
Connected texts are characterised by the presence of linguistic elements relating to shared referents throughout the text. These elements together form a structure that lends cohesion to the text. The realisation of those cohesive structures is subject to different constraints and varying preferences in different languages. We regularly observe mismatches of cohesive structures across languages in parallel texts. This can be a result of either a divergence of language-internal constraints or of effects of the translation process. As fully automatic high-quality MT is starting to look achievable, the question arises how cohesive elements should be handled in MT evaluation, since the common assumption of 1:1 correspondence between referring expressions is a poor match for what we find in corpus data. Focusing on the translation of pronouns, I discuss different approaches to evaluating a particular type of cohesive elements in MT output and the trade-offs they make between evaluation cost, validity, specificity and coverage. I suggest that a meaningful evaluation of cohesive structures in translation is difficult to achieve simply by appealing to the intuition of human annotators, but requires a more structured approach that forces us to make up our minds about the standards we expect the translation output to adhere to.- Anthology ID:
- 2020.iwdp-1.10
- Volume:
- Proceedings of the Second International Workshop of Discourse Processing
- Month:
- December
- Year:
- 2020
- Address:
- Suzhou, China
- Editors:
- Qun Liu, Deyi Xiong, Shili Ge, Xiaojun Zhang
- Venue:
- iwdp
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 54
- Language:
- URL:
- https://aclanthology.org/2020.iwdp-1.10
- DOI:
- Cite (ACL):
- Christian Hardmeier. 2020. Referential Cohesion A Challenge for Machine Translation Evaluation. In Proceedings of the Second International Workshop of Discourse Processing, page 54, Suzhou, China. Association for Computational Linguistics.
- Cite (Informal):
- Referential Cohesion A Challenge for Machine Translation Evaluation (Hardmeier, iwdp 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.iwdp-1.10.pdf