Abstract
The paper presents experimental results on automatic word sense disambiguation (WSD). Contexts for polysemous and/or homonymic Russian nouns denoting physical objects serve as an empirical basis of the study. Sets of contexts were extracted from the Russian National Corpus (RNC). Machine learning software for WSD was developed within the framework of the project. WSD tool used in experiments is aimed at statistical processing and classification of noun contexts. WSD procedure was performed taking into account lexical markers of word meanings in contexts and semantic annotation of contexts. Sets of experiments allowed to define optimal conditions for WSD in Russian texts.
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Mitrofanova, O., Lashevskaya, O., Panicheva, P. (2008). Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_21
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DOI: https://doi.org/10.1007/978-3-540-87391-4_21
Publisher Name: Springer, Berlin, Heidelberg
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