Context Dependent Semantic Parsing: A Survey

TL;DR

This survey reviews recent progress in context-dependent semantic parsing, highlighting methods, datasets, challenges, and future directions for incorporating contextual information to improve natural language understanding.

Contribution

It provides a comprehensive overview of current approaches, datasets, and open challenges in the emerging field of context-dependent semantic parsing.

Findings

Significant progress in modeling context for semantic parsing

Existing datasets support various dialogue and comment-based tasks

Open problems include handling long contexts and diverse language use

Abstract

Semantic parsing is the task of translating natural language utterances into machine-readable meaning representations. Currently, most semantic parsing methods are not able to utilize contextual information (e.g. dialogue and comments history), which has a great potential to boost semantic parsing performance. To address this issue, context dependent semantic parsing has recently drawn a lot of attention. In this survey, we investigate progress on the methods for the context dependent semantic parsing, together with the current datasets and tasks. We then point out open problems and challenges for future research in this area. The collected resources for this topic are available at:https://github.com/zhuang-li/Contextual-Semantic-Parsing-Paper-List.