@inproceedings{azerkovich-2019-using,
    title = "Using Thesaurus Data to Improve Coreference Resolution for {R}ussian",
    author = "Azerkovich, Ilya",
    editor = "Vossen, Piek  and
      Fellbaum, Christiane",
    booktitle = "Proceedings of the 10th Global Wordnet Conference",
    month = jul,
    year = "2019",
    address = "Wroclaw, Poland",
    publisher = "Global Wordnet Association",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2019.gwc-1.6/",
    pages = "39--45",
    abstract = "Semantic information about entities, specifically, how close in meaning two mentions are to each other, can become very useful for the task of co-reference resolution. One of the most well-researched and widely used forms of presenting this information are measures of semantic similarity and semantic relatedness. These metrics are often computed, relying upon the structure of a thesaurus, but it is also possible to use alternative resources. One such source is Wikipedia, which possesses the category structure similar to that of a thesaurus. In this work we describe an attempt to use semantic relatedness measures, calculated on thesaurus and Wikipedia data, to improve the quality of a co-reference resolution system for Russian language. The results show that this is a viable solution and that combining the two sources yields the most gain in quality."
}