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Part-of-Speech Driven Cross-Lingual Pronoun Prediction with Feed-Forward Neural Networks

  • 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-review

Original language

English

Publication milestones

  • Published - 21/09/2015

Publication status

Published - 21/09/2015
978-1-941643-32-7

Publication IDs

  • ORCID: /0000-0002-6103-7275/work/106363242
  • Scopus: 85001032254

Host publication title

Proceedings of the Second Workshop on Discourse in Machine Translation

Abstract

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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