On one hand, the decent precision shows potentials of the KG-Net to capture patterns with entity-sequence and KG information.
we suggest that the weakness of the KG-Net might be caused by the sparsity of entity-sequence space (the dataset scales down after word-to-entity mapping), and we can enhance it by exploring other information such as relational paths (Lin et al., 2015;Zeng et al., 2017); (2) Corpus-Net achieves comparable results with CNN+ATT and PCNN+ATT, which reveals the effectiveness of Corpus-Net that could be the backbone of the CORD framework; (3) The CORD outperforms other methods on most recall area, demonstrating the effectiveness of our methods.