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https://scholarbank.nus.edu.sg/handle/10635/41953
Title: | Feature-rich named entity recognition for bulgarian using conditional random fields | Authors: | Georgiev, G. Nakov, P. Ganchev, K. Osenova, P. Simov, K. |
Keywords: | Conditional random fields Information extraction Linear models Machine learning Morphology Named entity recognition |
Issue Date: | 2009 | Citation: | Georgiev, G.,Nakov, P.,Ganchev, K.,Osenova, P.,Simov, K. (2009). Feature-rich named entity recognition for bulgarian using conditional random fields. International Conference Recent Advances in Natural Language Processing, RANLP : 113-117. ScholarBank@NUS Repository. | Abstract: | The paper presents a feature-rich approach to the automatic recognition and categorization of named entities (persons, organizations, locations, and miscellaneous) in news text for Bulgarian. We combine well-established features used for other languages with language-specific lexical, syntactic and morphological information. In particular, we make use of the rich tagset annotation of the BulTreeBank (680 morpho-syntactic tags), from which we derive suitable task-specific tagsets (local and nonlocal). We further add domain-specific gazetteers and additional unlabeled data, achieving F 1=89.4%, which is comparable to the state-of-the-art results for English. | Source Title: | International Conference Recent Advances in Natural Language Processing, RANLP | URI: | http://scholarbank.nus.edu.sg/handle/10635/41953 | ISSN: | 13138502 |
Appears in Collections: | Staff Publications |
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