Abstract
This paper addresses the task of predicting the correct French translations of third-person subject pronouns in English discourse, a problem that is relevant as a prerequisite for machine translation and that requires anaphora resolution. We present an approach based on neural networks that models anaphoric links as latent variables and show that its performance is competitive with that of a system with separate anaphora resolution while not requiring any coreference-annotated training data. This demonstrates that the information contained in parallel bitexts can successfully be used to acquire knowledge about pronominal anaphora in a supervised way.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing |
| Publication date | 21 Oct 2013 |
| ISBN (Print) | 978-1-937284-97-8 |
| Publication status | Published - 21 Oct 2013 |
| Externally published | Yes |