Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
Table 3: Best kNN models vs. most frequent sense (MFS) and state of the art (F1%). Best results are bold, previous SOTA is in italics and our best results are underlined.
['[BOLD] k', '[BOLD] SE-2', '[BOLD] SE-3', '[BOLD] S7-T7', '[BOLD] S7-T17']
For SensEval-2 and SensEval-3, we achieve a new state-of-the-art result. We observe convergence with higher k values since our k′ normalization heuristic is activated. For the S7-T *, we also achieve minor improvements with a higher k, but still drastically lack behind the state of the art.