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.
Originalsprog | Engelsk |
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Titel | Proceedings of the Second Workshop on Discourse in Machine Translation |
Publikationsdato | 21 sep. 2015 |
ISBN (Trykt) | 978-1-941643-32-7 |
DOI | |
Status | Udgivet - 21 sep. 2015 |
Udgivet eksternt | Ja |