Abstract / Description of output
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.
Original language | English |
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Title of host publication | Proceedings of the Second Workshop on Discourse in Machine Translation |
Place of Publication | Lisbon, Portugal |
Publisher | Association for Computational Linguistics |
Pages | 59-64 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-941643-32-7 |
DOIs | |
Publication status | Published - 21 Sept 2015 |
Event | Second Workshop on Discourse in Machine Translation - Lisbon, Portugal Duration: 17 Sept 2015 → 17 Sept 2015 http://www.emnlp2015.org/proceedings/DiscoMT/index.html |
Workshop
Workshop | Second Workshop on Discourse in Machine Translation |
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Abbreviated title | DiscoMT 2015 |
Country/Territory | Portugal |
City | Lisbon |
Period | 17/09/15 → 17/09/15 |
Internet address |