Learning Distributed Representations of Texts and Entities from Knowledge Base
Table 4: Accuracies of the proposed method and the state-of-the-art methods.
['[EMPTY]', 'CoNLL (Micro)', 'CoNLL (Macro)', 'TAC10 (Micro)']
Our method achieved strong results on both the CoNLL and the TAC 2010 datasets. In particular, the NTEE model clearly outperformed the other proposed models. We also tested the performance of the NTEE model without using the string similarity features (strsim) and found that these features also contributed to the performance.