AAAI 2006
An End-to-End Supervised Target-Word Sense Disambiguation System
Abstract
We present an extensible supervised Target-Word Sense Disambiguation system that leverages upon GATE (General Architecture for Text Engineering), NSP (Ngram Statistics Package) and WEKA (Waikato Environment for Knowledge Analysis) to present an end-toend solution that integrates feature identification, feature extraction, preprocessing and classification.
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Keywords
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Context
- Venue
- AAAI Conference on Artificial Intelligence
- Archive span
- 1980-2026
- Indexed papers
- 28718
- Paper id
- 624282299815661020