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A Study on Bilingually Informed Coreference Resolution

Publication at Faculty of Mathematics and Physics |
2018

Abstract

Coreference is a basic means to retain coherence of a text that likely exists in every language. However, languages may differ in how a coreference relation is manifested on the surface.

A possible way how to measure the extent and nature of such differences is to build a coreference resolution system that operates on a parallel corpus and extracts information from both language sides of the corpus. In this work, we build such a bilingually informed coreference resolution system and apply it on Czech-English data.

We compare its performance with the system that learns only from a single language. Our results show that the cross-lingual approach outperforms the monolingual one.

They also suggest that a system for Czech can exploit the additional English information more effectively than the other way round. The work concludes with a detailed analysis that tries to reveal the reasons behind these results.