Semi-automatic Lexicalized Tree Adjoining Grammar Extraction towards Natural Language Generation

DOI

10.2991/amcce-15.2015.42How to use a DOI?

Keywords

Lexicalized Tree Adjoining Grammar; Grammar Extraction

Abstract

Deep grammar Formalism such as Tree Adjoining Grammar(TAG) is widely used in Natural Language Generation(NLG). However, crafting the grammar not only requires expert knowledge of both the grammar formalism and the target application domain of NLG, but also needs a lot of human labor. In this paper, we propose a semi-automatic approach to extract well-formed Lexicalized Tree Adjoining Grammar(LTAG) anchored with proper semantics from a parallel corpus. The parallel cor- pus consists of sentences and the correspondent semantics. This approach requires much less human effort. The result shows that our approach achieves comparable performance with the state-of-the-art. Meanwhile, the grammar extracted in this paper has better linguistic interpretation than previous work.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wei Qiu
AU  - Tianfang Yao
PY  - 2015/04
DA  - 2015/04
TI  - Semi-automatic Lexicalized Tree Adjoining Grammar Extraction towards Natural Language Generation
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 231
EP  - 236
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.42
DO  - 10.2991/amcce-15.2015.42
ID  - Qiu2015/04
ER  -