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Extraction of templates from phrases using Sequence Binary Decision Diagrams

Published online by Cambridge University Press:  19 July 2018

D. HIRANO ,
K. TANAKA-ISHII  and
A. FINCH
D. HIRANO
Affiliation:
Graduate School and Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan e-mail: hirano@limu.ait.kyushu-u.ac.jp
K. TANAKA-ISHII
Affiliation:
Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan e-mail: kumiko@cl.rcast.u-tokyo.ac.jp
A. FINCH
Affiliation:
National Institute of Information and Communications Technology Kyoto, Kyoto, Japan e-mail: andrew.finch@gmail.com
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Abstract

The extraction of templates such as ‘regard X as Y’ from a set of related phrases requires the identification of their internal structures. This paper presents an unsupervised approach for extracting templates on-the-fly from only tagged text by using a novel relaxed variant of the Sequence Binary Decision Diagram (SeqBDD). A SeqBDD can compress a set of sequences into a graphical structure equivalent to a minimal deterministic finite state automata, but more compact and better suited to the task of template extraction. The main contribution of this paper is a relaxed form of the SeqBDD construction algorithm that enables it to form general representations from a small amount of data. The process of compression of shared structures in the text during Relaxed SeqBDD construction, naturally induces the templates we wish to extract. Experiments show that the method is capable of high-quality extraction on tasks based on verb+preposition templates from corpora and phrasal templates from short messages from social media.

Type
Article
Information
Natural Language Engineering , Volume 24 , Issue 5 , September 2018 , pp. 763 - 795
Copyright
Copyright © Cambridge University Press 2018 

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