Joint Neural Entity Disambiguation with Output Space Search
Table 2: Evaluation on CoNLL 2003 Test-b and TAC-2010
['[BOLD] models', '[BOLD] In-KB acc%']
To evaluate the model performance we use the standard micro-average accuracies of the top-ranked candidate entities. We use different alias mappings for TAC and CoNLL. Specifically, for TAC we only use anchor-title alias mappings constructed from hyper-links in the Wikipedia. (b) show our performance on the CoNLL and TAC datasets for our local and global models along with other competitive systems respectively. The results show that our global model outperforms all the competitors for both CoNLL 2003 and TAC 2010. It is interesting to note that our local model is solid, but is noticeably inferior to the stat-of-the-art local model.