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 |
|---|---|
| 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 |