A Discourse-Level Named Entity Recognition and Relation Extraction Dataset for Chinese Literature Text
Table 3: Results of Named Entity Recognition on the proposed corpus.
['Models', '[EMPTY]', 'Thing', 'Person', 'Location', 'Organization', 'Time', 'Metric', 'All']
It can be clearly seen that CRF achieves the better performance than Bi-LSTM on all tags, which probably be attributed to the feature template.