Pronoun Prediction with Latent Anaphora Resolution

Christian Hardmeier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes the UU-Hardmeier submissions to the WMT 2016 shared task on cross-lingual pronoun prediction. Our model is a system combination of two different approaches, one based on a neural network with latent anaphora resolution and the other one on an n-gram model with an additional dependency on the source pronoun. The combination of the two models results in an improvement over each individual system, but it appears that the contribution of the neural network is more likely due to its context modelling capacities than to the anaphora resolution subnetwork.
Original languageEnglish
Title of host publicationProceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers
Place of PublicationBerlin, Germany
PublisherAssociation for Computational Linguistics
Pages576-580
Number of pages5
DOIs
Publication statusPublished - 12 Aug 2016
EventFirst Conference on Machine Translation - Berlin, Germany
Duration: 11 Aug 201612 Aug 2016
http://www.statmt.org/wmt16/

Conference

ConferenceFirst Conference on Machine Translation
Abbreviated titleWMT16
CountryGermany
CityBerlin
Period11/08/1612/08/16
Internet address

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