Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks

Understand

Textual entailment is a fundamental task in natural language processing.

• Most approaches for solving the problem use only the textual content present in training data.
• A few approaches have shown that information from external knowledge sources like knowledge graphs (KGs) can add value, in addition to the textual content, by providing background knowledge that may be critical for a task.
• However, the proposed models do not fully exploit the information in the usually large and noisy KGs, and it is not clear how it can be effectively encoded to be useful for entailment.