Using multiple knowledge sources for word sense discrimination
Computational Linguistics
Computational Linguistics
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ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
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HLT '91 Proceedings of the workshop on Speech and Natural Language
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In this paper, we describe the acquisition and organization of knowledge sources for machine translation (MT) systems. It has been pointed out by many users that one of the most annoying things about MT systems is the repeated occurrence of identical errors in word sense and attachment disambignuation. We show the limitations of a conventional user-dictionary method and explain how our approach solves the problem.