A BiLSTM-based System for Cross-lingual Pronoun Prediction

Sara Stymne, Sharid Loáiciga, Fabienne Cap
<span title="">2017</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wiyp6rhsjbhrzl3gyyy6u5xcj4" style="color: black;">Proceedings of the Third Workshop on Discourse in Machine Translation</a> </i> &nbsp;
We describe the Uppsala system for the 2017 DiscoMT shared task on crosslingual pronoun prediction. The system is based on a lower layer of BiLSTMs reading the source and target sentences respectively. Classification is based on the BiLSTM representation of the source and target positions for the pronouns. In addition we enrich our system with dependency representations from an external parser and character representations of the source sentence. We show that these additions perform well for
more &raquo; ... man and Spanish as source languages. Our system is competitive and is in first or second place for all language pairs.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/w17-4805">doi:10.18653/v1/w17-4805</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/discomt/StymneLC17.html">dblp:conf/discomt/StymneLC17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v6qlj4ytvfan5ke73qh6nqxzd4">fatcat:v6qlj4ytvfan5ke73qh6nqxzd4</a> </span>
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