This paper presents a new open text word sense disambiguation method that combines the use of logical inferences with PageRank-style algorithms applied on graphs extracted from natural language documents. We evaluate the accuracy of the proposed algorithm on several sense-annotated texts, and show that it consistently outperforms the accuracy of other previously proposed knowledge-based word sense disambiguation methods. We also explore and evaluate methods that combine several open-text word sense disambiguation algorithms.
REF later applied PageRank to another problem of natural language processing, word sense disambiguation.
PageRank On Semantic Networks, With Application To Word Sense Disambiguation
International Conference On Computational Linguistics
Computer Science