Extracting named entities from Russian-language documents with different expressiveness of structure
| Autor: | Maria D. Averina, Olga A. Levanova |
|---|---|
| Jazyk: | English<br />Russian |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Моделирование и анализ информационных систем, Vol 30, Iss 4, Pp 382-393 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1818-1015 2313-5417 |
| DOI: | 10.18255/1818-1015-2023-4-382-393 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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