Supervised Complementary Entity Recognition with Augmented Key-value Pairs of Knowledge
Table 1: Comparison of different methods in precision, recall and F1-score
['Product', '[BOLD] CRF(-)DR P', '[BOLD] CRF(-)DR R', '[BOLD] CRF(-)DR F1', '[BOLD] CRF P', '[BOLD] CRF R', '[BOLD] CRF F1', '[BOLD] CRF-Init P', '[BOLD] CRF-Init R', '[BOLD] CRF-Init F1', '[BOLD] KCRF P', '[BOLD] KCRF R', '[BOLD] KCRF F1']
It significantly outperforms other methods on recall, which indicates that the expanded knowledge is helpful. CRF-Init performs better than CRF on most products, which indicates that knowledge-based features are better than primitive features in general. However, we notice that in order to get a higher recall, KCRF sacrifices its precision a lot. So how to further ensure that the expanded knowledge is of high quality to keep high precision is still an open problem.