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Using multiple Web resources and inference rules to classify Chinese word semantic relation

Shutian Ma (Department of Information Management, Nanjing University of Science and Technology, Nannjing, China)
Yingyi Zhang (Department of Information Management, Nanjing University of Science and Technology, Nannjing, China)
Chengzhi Zhang (Department of Information Management, Nanjing University of Science and Technology, Nannjing, China)

Information Discovery and Delivery

ISSN: 2398-6247

Article publication date: 21 May 2018

275

Abstract

Purpose

The purpose of this paper is to classify Chinese word semantic relations, which are synonyms, antonyms, hyponyms and meronymys.

Design/methodology/approach

Basically, four simple methods are applied, ontology-based, dictionary-based, pattern-based and morpho-syntactic method. The authors make good use of search engine to build lexical and semantic resources for dictionary-based and pattern-based methods. To improve classification performance with more external resources, they also classify the given word pairs in Chinese and in English at the same time by using machine translation.

Findings

Experimental results show that the approach achieved an average F1 score of 50.87 per cent, an average accuracy of 70.36 per cent and an average recall of 40.05 per cent over all classification tasks. Synonym and antonym classification achieved high accuracy, i.e. above 90 per cent. Moreover, dictionary-based and pattern-based approaches work effectively on final data set.

Originality/value

For many natural language processing (NLP) tasks, the step of distinguishing word semantic relation can help to improve system performance, such as information extraction and knowledge graph generation. Currently, common methods for this task rely on large corpora for training or dictionaries and thesauri for inference, where limitation lies in freely data access and keeping built lexical resources up-date. This paper builds a primary system for classifying Chinese word semantic relations by seeking new ways to obtain the external resources efficiently.

Keywords

Acknowledgements

This work is supported by Major Projects of National Social Science Fund (No. 16ZAD224), Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) (No. MJUKF201704) and Qing Lan Project. The authors also thank Chenglei Qin here to provide the clawer for Web corpora collections.

Citation

Ma, S., Zhang, Y. and Zhang, C. (2018), "Using multiple Web resources and inference rules to classify Chinese word semantic relation", Information Discovery and Delivery, Vol. 46 No. 2, pp. 120-126. https://doi.org/10.1108/IDD-03-2018-0010

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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