Senseval corpus: There are now many computer programs for automatically determining the sense of a word in context (Word Sense Disambiguation or WSD). The purpose of Senseval is to evaluate the strengths and weaknesses of such programs with respect to different words, different varieties of language, and different languages.
Keywords for this software
References in zbMATH (referenced in 10 articles )
Showing results 1 to 10 of 10.
- Mincă, Andrei: An overview for speeding up a knowledge-based word sense disambiguation method (2012)
- Navigli, Roberto; Ponzetto, Simone Paolo: BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network (2012)
- Turdakov, D. Yu.: Word sense disambiguation methods (2010) ioport
- Biemann, Chris: Unsupervised part-of-speech tagging in the large (2009) ioport
- Specia, Lucia; Srinivasan, Ashwin; Joshi, Sachindra; Ramakrishnan, Ganesh; Nunes, Maria Das Graças Volpe: An investigation into feature construction to assist word sense disambiguation (2009) ioport
- Saquete, E.; Ferrández, O.; Ferrández, S.; Martínez-Barco, P.; Muñoz, R.: Combining automatic acquisition of knowledge with machine learning approaches for multilingual temporal recognition and normalization (2008) ioport
- Martín-Valdivia, M. T.; Ureña-López, L. A.; García-Vega, M.: The learning vector quantization algorithm applied to automatic text classification tasks (2007)
- Suárez, Armando; Palomar, Manuel: Best feature selection for maximum entropy-based word sense disambiguation (2002)
- Calzolari, Nicoletta; Corazzari, Ornella; Zampolli, Antonio: Lexical-semantic tagging of an italian corpus (2001)
- Pedersen, Ted: Lexical semantic ambiguity resolution with bigram-based decision trees (2001)