Translating Pronouns with Latent Anaphora Resolution
2014 (English)Conference paper, Poster (Other academic)
We discuss the translation of anaphoric pronouns in statistical machine translation from English into French. Pronoun translation requires resolving the antecedents of the pronouns in the input, a classic discourse processing problem that is usually approached through supervised learning from manually annotated data. We cast cross-lingual pronoun prediction as a classification task and present a neural network architecture that incorporates the links between anaphors and potential antecedents as latent variables, allowing us to train the classifier on parallel text without explicit supervision for the anaphora resolver. We demonstrate that our approach works just as well for classification as using an external coreference resolver whereas its impact in a practical translation experiment is more limited.
Place, publisher, year, edition, pages
Language Technology (Computational Linguistics)
Research subject Computational Linguistics
IdentifiersURN: urn:nbn:se:uu:diva-241303OAI: oai:DiVA.org:uu-241303DiVA: diva2:778267
Workshop on Modern Machine Learning and Natural Language Processing (NIPS 2014), Montreal, Canada, 8-12 Dec 2014