A Document-Level SMT System with Integrated Pronoun Prediction
- Uppsala University
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review
Open access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPublication milestones
- Published - 21/09/2015
Publication status
Published - 21/09/2015
ISBN (Print)
978-1-941643-32-7Publication IDs
- ORCID: /0000-0002-6103-7275/work/106363222
- Scopus: 85123399766
Host publication title
Proceedings of the Second Workshop on Discourse in Machine TranslationAbstract
This paper describes one of Uppsala University’s submissions to the pronoun-focused machine translation (MT) shared task at DiscoMT 2015. The system is based on phrase-based statistical MT implemented with the document-level decoder Docent. It includes a neural network for pronoun prediction trained with latent anaphora resolution. At translation time, coreference information is obtained from the Stanford CoreNLP system.
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