Identification of Singleton Mentions in Russian
Статья посвящена Форуму по оценке систем автоматического распознавания анафоры и кореферентности
Many NLP researchers, especially those not working in the area of discourse processing, tend to equate coreference resolution with the sort of coreference that people did in MUC, ACE, and OntoNotes, having the impression that coreference is a well-worn task owing in part to the large number of papers reporting results on the MUC/ACE/OntoNotes corpora. Given the plethora of work on entity coreference and aware of other fora gathering coreferencerelated papers (such as LAW, DiscoMT or EVENTS), we believed that time was ripe for a new workshop on the single topic of coreference resolution that would bring together researchers who were interested in under-investigated coreference phenomena, willing to contribute both theoretical and applied computational work on coreference resolution, especially for languages other than English, less-researched forms of coreference and new applications of coreference resolution.
Abstract - RU-EVAL is a biennial event organized in order to estimate the state of the art in Russian NLP resources, methods and toolkits and to compare various methods and principles implemented for Russian. Russian could be treated as an under-resourced language due to the lack of free distributable gold standard corpora for different NLP tasks (each team tried to work out their own standards). Thus, our goal was to work out the uniform basis for comparison of systems based on different theoretical and engineering approaches, to build evaluation resources, to provide a flexible system of evaluation in order to differentiate between non-acceptable and linguistically “admissible” errors. The paper reports on three events devoted to morphological tagging, dependency parsing and anaphora resolution, respectively.