/LING

Update: February 24, 2023 The new version of Termout.org is now online, so this web site is now obsolete and will soon be dismantled.

Lista de candidatos sometidos a examen:
1) lesk (*)
(*) Términos presentes en el nuestro glosario de lingüística

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1) Candidate: lesk

Is in goldstandard

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1
paper corpusSignosTxtLongLines455 - : First, the ABWSD method is compared against ^[123]Wang and Hirst (2014). They present a “Lesk-based algorithm which replaces the overlap mechanism of the Lesk algorithm with a general purpose Naive Bayes model” (^[124]Wang & Hirst, 2014: 1 ). The Naive Bayes model for word sense disambiguation (hereinafter known as NaiveBayesSM), computes the a posteriori probabilities of the senses of a polysemous word, then, the sense of the greater probability is chosen as the correct one. The experiments performed in ^[125]Wang and Hirst (2014) use the gloss description as the information source, a one-sentence context window, and stemming of the words in glosses and context. [126]Table 5 shows the F-score for the NaiveBayesSM and the ABWSD methods over the Senseval-2 corpus. For this comparison, the ABWSD methods were fitted with a random selection strategy for those cases when it is not able to provide an answer.

Evaluando al candidato lesk:

1) abwsd: 3
2) hirst: 3
3) wang: 3

lesk
Lengua:
Frec: 11
Docs: 3
Nombre propio: 1 / 11 = 9%
Coocurrencias con glosario:
Puntaje: 0.943 = ( + (1+3.32192809488736) / (1+3.58496250072116)));
Candidato aceptado

Referencias bibliográficas encontradas sobre cada término

(Que existan referencias dedicadas a un término es también indicio de terminologicidad.)

lesk

: Banerjee, S. & Pedersen, T. (2002). An adapted lesk algorithm for word sense disambiguation using wordnet. Proceedings of the CICLing 2002 Conference (pp. 136-145). LNCS: Springer-Verlag. : Basile, P., Caputo, A. & Semeraro, G. (2014). An enhanced lesk word sense disambiguation algorithm through a distributional semantic model. Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers (pp. 1591-1600). : Lesk, M. (1986). Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. Proceedings of the 5th annual international conference on Systems documentation (pp. 24-26). ACM.