Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Acquisition of categorized named entities for web search
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Fine grained classification of named entities
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
University of Sheffield: description of the LaSIE system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Fine-grained proper noun ontologies for question answering
SEMANET '02 Proceedings of the 2002 workshop on Building and using semantic networks - Volume 11
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
A language independent approach for name categorization and discrimination
ACL '07 Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
Fine-grained classification of named entities exploiting latent semantic kernels
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
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Named Entity Recognition became the basis of many Natural Language Processing applications. However, the existing coarse-grained named entity recognizers are insufficient for complex applications such as Question Answering, Internet Search engines or Ontology population. In this paper, we propose a domain distribution approach according to which names which occur in the same domains belong to the same fine-grained category. For our study, we generate a relevant domain resource by mapping and ranking the words from the WordNet glosses to their WordNet-Domains. This approach allows us to capture the semantic information of the context around the named entity and thus to discover the corresponding fine-grained name category. The presented approach is evaluated with six different person names and it reaches 73% f-score. The obtained results are encouraging and perform significantly better than a majority baseline.