Veska Noncheva


Extracting Named Entities. A Statistical Approach
Joaquim Silva | Zornitsa Kozareva | Veska Noncheva | Gabriel Lopes
Actes de la 11ème conférence sur le Traitement Automatique des Langues Naturelles. Posters

Named entities and more generally Multiword Lexical Units (MWUs) are important for various applications. However, language independent methods for automatically extracting MWUs do not provide us with clean data. So, in this paper we propose a method for selecting possible named entities from automatically extracted MWUs, and later, a statistics-based language independent unsupervised approach is applied to possible named entities in order to cluster them according to their type. Statistical features used by our clustering process are described and motivated. The Model-Based Clustering Analysis (MBCA) software enabled us to obtain different clusters for proposed named entities. The method was applied to Bulgarian and English. For some clusters, precision is very high; other clusters still need further refinement. Based on the obtained clusters, it is also possible to classify new possible named entities.


Automatic Acquisition of Word Interaction Patterns from Corpora
Veska Noncheva | Joaqium Ferreira da Silva | Gabriel Lopes
Proceedings of the 2003 EACL Workshop on Language Modeling for Text Entry Methods


Intelligent Handling of Weather Forecasts
Stephan Kerpedjiev | Veska Noncheva
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics