Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
Table 2: SynGCN Extrinsic Evaluation: Comparison on parts-of-speech tagging (POS), question answering (SQuAD), named entity recognition (NER), and co-reference resolution (Coref). SynGCN performs comparable or outperforms all existing approaches on all tasks. Refer Section 9.1 for details.
['Method', 'POS', 'SQuAD', 'NER', 'Coref']
Overall, we find that SynGCN either outperforms or performs comparably to other methods on all four tasks. Compared to the sequential context based methods, dependency based methods perform superior at question answering task as they effectively encode syntactic information. This is consistent with the observation of Peters et al.