Papers › SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings
SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings
Zhuosheng Zhang, Jiangtong Li, Hai Zhao, Bingjie Tang
This paper describes a hypernym discovery system for our participation in the SemEval-2018 Task 9, which aims to discover the best (set of) candidate hypernyms for input concepts or entities, given the search space of a pre-defined vocabulary. We introduce a neural network architecture for the concerned task and empirically study various neural network models to build the representations in latent space for words and phrases. The evaluated models include convolutional neural network, long-short term memory network, gated recurrent unit and recurrent convolutional neural network. We also explore different embedding methods, including word embedding and sense embedding for better performance.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Hypernym Discovery | General | SJTU BCMI | MAP | 5.77 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | General | SJTU BCMI | MRR | 10.56 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | General | SJTU BCMI | P@5 | 5.96 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | Medical domain | SJTU BCMI | MAP | 11.69 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | Medical domain | SJTU BCMI | MRR | 25.95 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | Medical domain | SJTU BCMI | P@5 | 11.69 | #6 of 8 | Archive leaderboard | report |
| Hypernym Discovery | Music domain | SJTU BCMI | MAP | 4.71 | #5 of 7 | Archive leaderboard | report |
| Hypernym Discovery | Music domain | SJTU BCMI | MRR | 9.15 | #5 of 7 | Archive leaderboard | report |
| Hypernym Discovery | Music domain | SJTU BCMI | P@5 | 4.91 | #5 of 7 | 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.
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