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.
2015. Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus. Natural Language Engineering 21:3 ► pp. 355 ff.
Ramírez-Cruz, Yunior & Aurora Pons-Porrata
2008. Spanish Nested Named Entity Recognition Using a Syntax-Dependent Tree Traversal-Based Strategy. In MICAI 2008: Advances in Artificial Intelligence [Lecture Notes in Computer Science, 5317], ► pp. 144 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.
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.
Ferrández, Óscar, Antonio Toral & Rafael Muñoz
2006. Fine Tuning Features and Post-processing Rules to Improve Named Entity Recognition. In Natural Language Processing and Information Systems [Lecture Notes in Computer Science, 3999], ► pp. 176 ff.
Kozareva, Zornitsa, Oscar Ferrández, Andres Montoyo, Rafael Muñoz & Armando Suárez
2005. Combining Data-Driven Systems for Improving Named Entity Recognition. In Natural Language Processing and Information Systems [Lecture Notes in Computer Science, 3513], ► pp. 80 ff.
Vicente, Montserrat Rangel
2005. La glose comme outil de désambiguïsation référentielle des noms propres purs. Corela :HS-2
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