Improving Sequence-to-Sequence Semantic Parser for Task Oriented Dialog

Chaoting Xuan


Abstract
Task Oriented Parsing (TOP) attempts to map utterances to compositional requests, including multiple intents and their slots. Previous work focus on a tree-based hierarchical meaning representation, and applying constituency parsing techniques to address TOP. In this paper, we propose a new format of meaning representation that is more compact and amenable to sequence-to-sequence (seq-to-seq) models. A simple copy-augmented seq-to-seq parser is built and evaluated over a public TOP dataset, resulting in 3.44% improvement over prior best seq-to-seq parser (exact match accuracy), which is also comparable to constituency parsers’ performance.
Anthology ID:
2020.intexsempar-1.3
Volume:
Proceedings of the First Workshop on Interactive and Executable Semantic Parsing
Month:
November
Year:
2020
Address:
Online
Editors:
Ben Bogin, Srinivasan Iyer, Xi Victoria Lin, Dragomir Radev, Alane Suhr, Panupong, Caiming Xiong, Pengcheng Yin, Tao Yu, Rui Zhang, Victor Zhong
Venue:
intexsempar
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
18–22
Language:
URL:
https://aclanthology.org/2020.intexsempar-1.3
DOI:
10.18653/v1/2020.intexsempar-1.3
Bibkey:
Cite (ACL):
Chaoting Xuan. 2020. Improving Sequence-to-Sequence Semantic Parser for Task Oriented Dialog. In Proceedings of the First Workshop on Interactive and Executable Semantic Parsing, pages 18–22, Online. Association for Computational Linguistics.
Cite (Informal):
Improving Sequence-to-Sequence Semantic Parser for Task Oriented Dialog (Xuan, intexsempar 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.intexsempar-1.3.pdf
Video:
 https://slideslive.com/38939455
Code
 cxuan2019/top