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We introduce an iterative approach to subgraph-based Word Sense Disambiguation (WSD). Inspired by the Sudoku puzzle, it significantly improves the precision and recall of disambiguation. We describe how conventional subgraph-based WSD treats the two steps of (1) subgraph construction and (2) disambiguation via graph centrality measures as ordered and atomic. Consequently, researchers tend to focus on improving either of these two steps individually, overlooking the fact that these steps can complement each other if they are allowed to interact in an iterative manner. We tested our iterative approach against the conventional approach for a range of well-known graph centrality measures and subgraph types, at the sentence and document level. The results demonstrated that an average performing WSD system which embraces the iterative approach, can easily compete with state-ofthe-art. This alone warrants further investigation.
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Manion et al. (2014) studied this question.