MICE
A module for Named Entities Recognition and Classification
Montserrat Arévalo Rodríguez | Universitat de Barcelona, Spain
Montserrat Civit Torruella | Universitat de Barcelona, Spain
Maria Antònia Martí | Universitat de Barcelona, Spain
In the field of corpus linguistics, Named Entity treatment includes the recognition and classification of different types of discursive elements like proper names, date, time, etc. These discursive elements play an important role in different Natural Language Processing applications and techniques such as Information Retrieval, Information Extraction, translations memories, document routers, etc.
Keywords: Named Entity Recognition and Classification, corpus linguistics, Information Extraction, Information Retrieval, semantic classification
Published online: 29 April 2004
https://doi.org/10.1075/ijcl.9.1.03are
https://doi.org/10.1075/ijcl.9.1.03are
Cited by
Cited by 6 other publications
Ferrández, Óscar, Antonio Toral & Rafael Muñoz
2006.
In Natural Language Processing and Information Systems [Lecture Notes in Computer Science, 3999],
► pp. 176 ff. 
Kozareva, Z., O. Ferrández, A. Montoyo, R. Muñoz, A. Suárez & J. Gómez
2007. Combining data-driven systems for improving Named Entity Recognition.
Data & Knowledge Engineering 61:3 ► pp. 449 ff.
Kozareva, Zornitsa, Oscar Ferrández, Andres Montoyo, Rafael Muñoz & Armando Suárez
2005.
In Natural Language Processing and Information Systems [Lecture Notes in Computer Science, 3513],
► pp. 80 ff.
Ramírez-Cruz, Yunior & Aurora Pons-Porrata
2008.
In MICAI 2008: Advances in Artificial Intelligence [Lecture Notes in Computer Science, 5317],
► pp. 144 ff.
Ruiz-Casado, Maria, Enrique Alfonseca & Pablo Castells
2007. Automatising the learning of lexical patterns: An application to the enrichment of WordNet by extracting semantic relationships from Wikipedia.
Data & Knowledge Engineering 61:3 ► pp. 484 ff.
VILA, M., H. RODRÍGUEZ & M. A. MARTÍ
2015. Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus.
Natural Language Engineering 21:3 ► pp. 355 ff.
This list is based on CrossRef data as of 14 january 2023. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.