Abstract
This paper considers various features for extracting named entities from texts in Russian, which are used within the approaches based on machine learning, including the features of a token itself (lexeme), as well as vocabulary, contextual, cluster, and two-stage features. The contribution of each feature to improving the quality of extraction of named entities is studied. The CRF-classifier is used as a method of machine learning in the experiments that are described in this paper. The contribution of features is compared based on two open collections using the F-measure.
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Original Russian Text © V.A. Mozharova, N.V. Lukashevich, 2017, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2: Informatsionnye Protsessy i Sistemy, 2017, No. 5, pp. 14–21.
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Mozharova, V.A., Lukashevich, N.V. Investigation of features for extraction of named entities from texts in Russian. Autom. Doc. Math. Linguist. 51, 127–134 (2017). https://doi.org/10.3103/S0005105517030049
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DOI: https://doi.org/10.3103/S0005105517030049