Papers › GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge
GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge
Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang
Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based methods. Recent studies have shown the effectiveness of incorporating gloss (sense definition) into neural networks for WSD. However, compared with traditional word expert supervised methods, they have not achieved much improvement. In this paper, we focus on how to better leverage gloss knowledge in a supervised neural WSD system. We construct context-gloss pairs and propose three BERT-based models for WSD. We fine-tune the pre-trained BERT model on SemCor3.0 training corpus and the experimental results on several English all-words WSD benchmark datasets show that our approach outperforms the state-of-the-art systems.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Entity Linking | WiC-TSV | GlossBert-ws | Task 1 Accuracy: all | 75.9 | #3 of 8 | Archive leaderboard | report |
| Entity Linking | WiC-TSV | GlossBert-ws | Task 1 Accuracy: domain specific | 76.7 | #3 of 8 | Archive leaderboard | report |
| Entity Linking | WiC-TSV | GlossBert-ws | Task 1 Accuracy: general purpose | 75.2 | #3 of 8 | Archive leaderboard | report |
| Word Sense Disambiguation | Supervised: | GlossBERT | SemEval 2007 | 72.5 | #15 of 27 | Archive leaderboard | report |
| Word Sense Disambiguation | Supervised: | GlossBERT | SemEval 2013 | 76.1 | #15 of 27 | Archive leaderboard | report |
| Word Sense Disambiguation | Supervised: | GlossBERT | SemEval 2015 | 80.4 | #15 of 27 | Archive leaderboard | report |
| Word Sense Disambiguation | Supervised: | GlossBERT | Senseval 2 | 77.7 | #15 of 27 | Archive leaderboard | report |
| Word Sense Disambiguation | Supervised: | GlossBERT | Senseval 3 | 75.2 | #15 of 27 | Archive leaderboard | report |
| Word Sense Disambiguation | WiC-TSV | GlossBert-ws | Task 1 Accuracy: all | 75.9 | #3 of 8 | Archive leaderboard | report |
| Word Sense Disambiguation | WiC-TSV | GlossBert-ws | Task 1 Accuracy: domain specific | 76.7 | #3 of 8 | Archive leaderboard | report |
| Word Sense Disambiguation | WiC-TSV | GlossBert-ws | Task 1 Accuracy: general purpose | 75.2 | #3 of 8 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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