Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Entity-based cross-document coreferencing using the Vector Space Model
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
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
Fine-grained proper noun ontologies for question answering
SEMANET '02 Proceedings of the 2002 workshop on Building and using semantic networks - Volume 11
Combining data-driven systems for improving Named Entity Recognition
Data & Knowledge Engineering
Name discrimination by clustering similar contexts
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Domain information for fine-grained person name categorization
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
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We present a language independent approach for fine-grained categorization and discrimination of names on the basis of text semantic similarity information. The experiments are conducted for languages from the Romance (Spanish) and Slavonic (Bulgarian) language groups. Despite the fact that these languages have specific characteristics as word-order and grammar, the obtained results are encouraging and show that our name entity method is scalable not only to different categories, but also to different languages. In an exhaustive experimental evaluation, we have demonstrated that our approach yields better results compared to a baseline system.