Part-of-Speech Driven Cross-Lingual Pronoun Prediction with Feed-Forward Neural Networks
- Jimmy Callin,
- ,
- Jörg Tiedemann
- Uppsala University
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen 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/106363242
- Scopus: 85001032254
Host publication title
Proceedings of the Second Workshop on Discourse in Machine TranslationAbstract
For some language pairs, pronoun translation is a discourse-driven task which requires information that lies beyond its local context. This motivates the task of predicting the correct pronoun given a source sentence and a target translation, where the translated pronouns have been replaced with placeholders. For cross-lingual pronoun prediction, we suggest a neural network-based model using preceding nouns and determiners as features for suggesting antecedent candidates. Our model scores on par with similar models while having a simpler architecture.
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