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The paper presents a feature-rich approach to the automatic recognition andcategorization of named entities (persons, organizations, locations, andmiscellaneous) in news text for Bulgarian. We combine well-established featuresused for other languages with language-specific lexical, syntactic andmorphological information. In particular, we make use of the rich tagsetannotation of the BulTreeBank (680 morpho-syntactic tags), from which we derivesuitable task-specific tagsets (local and nonlocal). We further adddomain-specific gazetteers and additional unlabeled data, achieving F1=89.4%,which is comparable to the state-of-the-art results for English.

Feature-Rich Named Entity Recognition for Bulgarian Using Conditional Random Fields