An End-to-end Supervised Target-Word Sense Disambiguation System

Mahesh Joshi, Serguei Pakhomov, Ted Pedersen, Richard Maclin, Christopher Chute

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-to-end solution that integrates feature identification, feature extraction, preprocessing and classification.

Subjects: 13. Natural Language Processing; 12. Machine Learning and Discovery

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