Misalignment of Semantic Relation Knowledge between WordNet and Human Intuition
This addresses a foundational issue for NLP researchers and lexicographers by highlighting discrepancies in a key resource, potentially guiding improvements to WordNet.
The study tackled the problem of misalignment between WordNet's semantic relations and human intuition, revealing a general mismatch and systematic patterns in synonymy and taxonomic relations, with WordNet path length not reliably indicating human judgments.
WordNet provides a carefully constructed repository of semantic relations, created by specialists. But there is another source of information on semantic relations, the intuition of language users. We present the first systematic study of the degree to which these two sources are aligned. Investigating the cases of misalignment could make proper use of WordNet and facilitate its improvement. Our analysis which uses templates to elicit responses from human participants, reveals a general misalignment of semantic relation knowledge between WordNet and human intuition. Further analyses find a systematic pattern of mismatch among synonymy and taxonomic relations~(hypernymy and hyponymy), together with the fact that WordNet path length does not serve as a reliable indicator of human intuition regarding hypernymy or hyponymy relations.