TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network
Table 4. Model performance on SemEval dataset. TaxoExpan versus all previous state-of-the-art methods. We report the best performance of all existing methods in the literature.
['[BOLD] Method', '[BOLD] Wu&P', '[BOLD] Recall', '[BOLD] F1']
We can see that both dist-XGBoost and TaxoExpan methods can outperform the previous winning system of this task (i.e., MSejrKU) and the baseline ETF. In addition, we can see the FWFS heuristic is indeed very powerful for this dataset and incorporating it as a strong feature can significantly boost the performance. However, this feature requires human-labeled definition sentences and thus can not be easily generalized to taxonomies other than WordNet. Finally, we show that TaxoExpan-FWFS can achieve the new state-of-the-art performance on this dataset.