Knowledge-Aware Conversational Semantic Parsing Over Web Tables

Understand

Conversational semantic parsing over tables requires knowledge acquiring and reasoning abilities, which have not been well explored by current state-of-the-art approaches.

• Motivated by this fact, we propose a knowledge-aware semantic parser to improve parsing performance by integrating various types of knowledge.
• In this paper, we consider three types of knowledge, including grammar knowledge, expert knowledge, and external resource knowledge.
• First, grammar knowledge empowers the model to effectively replicate previously generated logical form, which effectively handles the co-reference and ellipsis phenomena in conversation Second, based on expert knowledge, we propose a decomposable model, which is more controllable compared with traditional end-to-end models that put all the burdens of learning on trial-and-error in an end-to-end way.