A Unified Knowledge Based Approach for Sense Disambiguation and Semantic Role Labeling

Proceedings of the AAAI Conference on Artificial Intelligence, 21

Volume

Technical Papers

Knowledge Representation and Logic

In this paper, we present a unified knowledge based approach for sense disambiguation and semantic role labeling. Our approach performs both tasks through a single algorithm that matches candidate semantic interpretations to background knowledge to select the best matching candidate. We evaluate our approach on a corpus of sentences collected from various domains and show how our approach performs well on both sense disambiguation and semantic role labeling.