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|Title:||Feature-rich named entity recognition for bulgarian using conditional random fields||Authors:||Georgiev, G.
|Keywords:||Conditional random fields
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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