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Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

TOLDOVA, Svetlana  and  LONOV, Max. Mention Detection for Improving Coreference Resolution in Russian Texts: A Machine Learning Approach. Comp. y Sist. [online]. 2016, vol.20, n.4, pp.681-696. ISSN 2007-9737.  https://doi.org/10.13053/cys-20-4-2480.

Coreference resolution task is a well-known NLP application that was proven helpful for all high-level NLP applications: machine translation, summarization, and others. Mention detection is the sub-task of detecting the discourse status of each noun phrase, classifying it as a discourse-new, singleton (mentioned only once) or discourse-old occurrence. It has been shown that this task applied to a coreference resolution system may increase its overall performance. So, we decided to adapt current approaches for English language into Russian. We present some quality results of experiments regarding classifiers for mention detection and their application into the coreference resolution task in Russian languages.

Keywords : Coreference resolution; discourse-new detection; singleton detection; discourse processing; natural language processing; machine learning.

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