Abstract
Named-entity recognition (NER) involves the identification and classification of named entities in text. This is an important subtask in most language engineering applications, in particular information extraction, where different types of named entity are associated with specific roles in events. In this paper, we present a prototype NER system for Greek texts that we developed based on a NER system for English. Both systems are evaluated on corpora of the same domain and of similar size. The time-consuming process for the construction and update of domain-specific resources in both systems led us to examine a machine learning method for the automatic construction of such resources for a particular application in a specific language.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bikel, D.M., Miller, S., Schwartz, R., and Weischedel, R.: 1997, Nymble: A high-performance learning name-finder, in: Proc. of the 5th Conf. on Applied Natural Language Processing (ANLP-97), Washington, DC, 1997, pp. 194–201.
Brill, E.: 1993, A corpus-based approach to language learning, PhD Dissertation, University of Pennsylvania.
Cowie, J.: 1995, Description of the CRL/NMSU System Used for MUC-6, in: (DARPA, 1995).
Cuchiarelli, A., Luzi, D., and Velardi, P.: 1998, Automatic semantic tagging of unknown proper names, in: Proc. of COLING-98, Montreal, 1998.
Cunningham, H., Wilks, Y., and Gaizauskas, R.: 1996, GATE – a General Architecture for Text Engineering, in: Proc. of 16th Conf. on Computational Linguistics (COLING'96), 1996, pp. 274–279.
DARPA: Defense Advanced Research Projects Agency: 1995, in: Proc. of the 6th Message Understanding Conf. (MUC-6), Morgan Kaufmann, Los Altos, CA.
DARPA: Defense Advanced Research Projects Agency: 1998, in: Proc. of the 7th Message Understanding Conf. (MUC-7), Morgan Kaufmann, Los Altos, CA.
Day, D., Robinson, P., Vilain, M., and Yeh, A.: 1998, Description of the ALEMBIC system as used for MUC-7, in: (DARPA, 1998).
Gaizauskas, R. and Wilks, Y.: 1997, Information extraction beyond document retrieval, University of Sheffield, Department of Computer Science, CS–97–10.
Gazdar, G. and Mellish, C.: 1989, Natural Language Processing in Prolog, Addison-Wesley, Reading, MA.
Humphreys, K., Gaizauskas, R., Cunningham, H., and Azzam, S.: 1997, VIE Technical Specifications, Department of Computer Science, University of Sheffield.
Petasis, G., Paliouras, G., Karkaletsis, V., and Spyropoulos, C.D.: 1999, Resolving part-of-speech ambiguity in the Greek language using learning techniques, in: Proc. of ACAI'99 – Workshop on Machine Learning in Human Language Technology, Chania, Greece, July 1999.
Quinlan, J. R.: 1991, Machine learning: Easily understood decision rules, in: S. M. Weiss and C. A. Kulikowski (eds.), Computer Systems that Learn, Morgan Kaufmann, Los Altos, CA.
Quinlan, J. R.: 1993, C4.5: Programs for Machine Learning, Morgan Kaufmann, San Mateo, CA.
Sekine, S.: 1998, NYU: Description of the Japanese NE system used for MET-2, in: (DARPA, 1998).
Vilain, M. and Day, D.: 1996, Finite-state phrase parsing by rule sequences, in: Proc. of COLING-96, Vol. 1, pp. 274–279.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Karkaletsis, V., Paliouras, G., Petasis, G. et al. Named-Entity Recognition from Greek and English Texts. Journal of Intelligent and Robotic Systems 26, 123–135 (1999). https://doi.org/10.1023/A:1008124406923
Issue Date:
DOI: https://doi.org/10.1023/A:1008124406923