Combining Weak Knowledge Sources for Sense Disambiguation
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Natural Language Processing. Pages 884-888.
Abstract
There has been a tradition of combining different knowledge sources in Artificial Intelligence research. We apply this methodology to word sense disambiguation (WSD), a long-standing problem in Computational Linguistics. We report on an implemented sense tagger which uses a machine readable dictionary to provide both a set of senses and associated forms of information on which to base disambiguation decisions. The system is based on an architecture which makes use of different sources of lexical knowledge in two ways and optimises their combination using a learning algorithm. Tested accuracy of our approach on a general corpus exceeds 94%, demonstrating the viability of allword disambiguation as opposed to restricting oneself to a small sample.
@inproceedings{ijcai1999p126,
title = {Combining Weak Knowledge Sources for Sense Disambiguation},
author = {Stevenson, Mark and Wilks, Yorick},
booktitle = {Proceedings of the Sixteenth International Joint Conference on
Artificial Intelligence, {IJCAI-99}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Thomas Dean},
pages = {884--888},
year = {1999},
note = {Natural Language Processing},
url = {https://ijcai.org/proceedings/1999/126},
}
TY - CPAPER TI - Combining Weak Knowledge Sources for Sense Disambiguation AU - Stevenson, Mark AU - Wilks, Yorick T2 - Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 PB - International Joint Conferences on Artificial Intelligence PY - 1999 SP - 884 EP - 888 UR - https://ijcai.org/proceedings/1999/126 ER -Copied
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