2004 WordSenseDisambigUsingWordnetAndLesk

• (Ekehadl & Golub, 2004) ⇒ Jonas Ekedahl, Koraljka Golub. (2004). “Word Sense Disambiguation Using WordNet and the Lesk Algorithm.” Class Report. Language Processing and Computational Linguistics. Institutionen för datavetenskap.

Subject Headings: Word Sense Disambiguation Algorithm, Lesk Algorithm, WordNet.

Quotes

Abstract

• Word sense disambiguation is the process of automatically clarifying the meaning of a word in its context. It has drawn much interest in the last decade and much improved results are being obtained.
• In this paper we take the so-called Lesk approach. In our case, definitions of the senses of the words to be disambiguated, as well as of the ten surrounding nouns, adjectives and verbs, are derived and enriched using the WordNet lexical database.
• Two possible implications of this project could be that the results are dependent on the characteristics of a* test document and on the* characteristics of glosses, which needs to be further investigated. The average precision performed worse (0.45) than baseline precision (0.60) which was based on always electing the most frequent sense. However, the presented approach has several limitations: a small sample, and a big number of fine senses in WordNet, many of which are not that distinguishable from each other. The future work would include experimenting with different variations of the approach.

References

• Desire : Development of a European Service for Information on Research and Education. http://www.desire.org/.
• Domain Driven Disambiguation. http://wndomains.itc.it/download.html
• Ganesh Ramakrishnan, B. Prithviraj, Pushpak Bhattacharyya. A Gloss Centered Algorithm for Word Sense Disambiguation. Proceedings of the ACL SENSEVAL 2004, Barcelona, Spain. P. 217-221.
• Jones I., Cunliffe D., Tudhope D. (2004). Natural Language Processing and Knowledge Organization Systems as an aid to Retrieval. Proceedings 8th International Society of Knowledge Organization Conference (ISKO 2004), UCL London. (Ed: Ia C. McIlwaine), Advanced in knowledge Organization, 9, Ergon Verlag. P. 351-356.
• Michael E. Lesk. (1986). Automatic sense disambiguation: How to tell a pine cone from an ice cream cone. In: Proceedings of the 1986 SIGDOC Conference, pages 24−26, New York. Association for Computing Machinery.
• MXPOST : Maximum Entropy Part-Of-Speech Tagger, and MXPARSE: (local) Maximum Entropy Parser. http://www.cis.upenn.edu/~adwait/penntools.html#Tools
• Obtaining WordNet. http://www.cogsci.princeton.edu/~wn/obtain.shtml
• The Penn Treebank project. http://www.cis.upenn.edu/~treebank/
• (Banerjee, 2002) ⇒ Satanjeev Banerjee. (2002). “Adapting the Lesk algorithm for Word Sense Disambiguation to WordNet.” Master’s thesis. Dept. of Computer Science, University of Minnesota, USA.
• Senseval : evaluation exercises for Word Sense Disambiguation. http://www.senseval.org/
• Tokenizer.sed. http://www.cis.upenn.edu/~treebank/tokenizer.sed
• WordNet : a lexical database for the English language. http://www.cogsci.princeton.edu/~wn/,

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2004 WordSenseDisambigUsingWordnetAndLesk	Jonas Ekedahl Koraljka Golub			Word Sense Disambiguation Using WordNet and the Lesk Algorithm			http://www.cs.lth.se/EDA171/Reports/2004/jonas koraljka.pdf			2004