Geodesic
Extracting named entities from russian-language documents with different expressiveness of structure
Modelirovanie i analiz informacionnyh sistem, Tome 30 (2023) no. 4, pp. 382-393

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This work is devoted to solving the problem of recognizing named entities for Russian-language texts based on the CRF model. Two sets of data were considered: documents on refinancing with a good document structure, semi-structured texts of court records. The model was tested under various sets of text features and CRF parameters (optimization algorithms). In average for all entities, the best F-measure value for structured documents was 0.99, and for semi-structured ones 0.86.
Keywords: named entity extraction
Mots-clés : CRF. 
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     author = {M. D. Averina and O. A. Levanova},
     title = {Extracting named entities from russian-language documents with different expressiveness of structure},
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     pages = {382--393},
     publisher = {mathdoc},
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     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MAIS_2023_30_4_a5/}
}
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M. D. Averina; O. A. Levanova. Extracting named entities from russian-language documents with different expressiveness of structure. Modelirovanie i analiz informacionnyh sistem, Tome 30 (2023) no. 4, pp. 382-393. http://geodesic.mathdoc.fr/item/MAIS_2023_30_4_a5/