Expanding WordNet with Gloss and Polysemy Links for Evocation Strength Recognition

Evocation — a phenomenon of sense associations going beyond standard (lexico)-semantic relations — is difficult to recognise for natural language processing systems. Machine learning models give predictions which are only moderately correlated with the evocation strength. It is believed that ordinary graph measures are not as good at this task as methods based on vector representations. The paper proposes a new method of enriching the WordNet structure with weighted polysemy and gloss links, and proves that Dijkstra’s algorithm performs equally as well as other more sophisticated measures when set together with such expanded structures.