Abstract
This paper describes a first attempt at a statistical model for simultaneous syntactic parsing and generalized word-sense disambiguation. On a new data set we have constructed for the task, while we were disappointed not to find parsing improvement over a traditional parsing model, our model achieves a recall of 84.0% and a precision of 67.3% of exact synset matches on our test corpus, where the gold standard has a reported inter-annotator agreement of 78.6%.
Cite
CITATION STYLE
Bikel, D. M. (2000). A Statistical Model for Parsing and Word-Sense Disambiguation. In Proceedings of the 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, SIGDAT-EMNLP 2000 - Held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics, ACL 2000 (pp. 155–163). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1117794.1117814
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