Abstract
In this article, we provide several approaches to the automatic identification of parallel sentences that require sentence-external linguistic context to be correctly translated. Our long-term goal is to automatically construct a test set of context-dependent sentences in order to evaluate machine translation models designed to improve the translation of contextual, discursive phenomena. We provide a discussion and critique that show that current approaches do not allow us to achieve our goal, and suggest that for now evaluating individual phenomena is likely the best solution.- Anthology ID:
- 2018.jeptalnrecital-court.22
- Volume:
- Actes de la Conférence TALN. Volume 1 - Articles longs, articles courts de TALN
- Month:
- 5
- Year:
- 2018
- Address:
- Rennes, France
- Venue:
- JEP/TALN/RECITAL
- SIG:
- Publisher:
- ATALA
- Note:
- Pages:
- 393–400
- Language:
- URL:
- https://aclanthology.org/2018.jeptalnrecital-court.22
- DOI:
- Cite (ACL):
- Rachel Bawden, Thomas Lavergne, and Sophie Rosset. 2018. Detecting context-dependent sentences in parallel corpora. In Actes de la Conférence TALN. Volume 1 - Articles longs, articles courts de TALN, pages 393–400, Rennes, France. ATALA.
- Cite (Informal):
- Detecting context-dependent sentences in parallel corpora (Bawden et al., JEP/TALN/RECITAL 2018)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2018.jeptalnrecital-court.22.pdf