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Predicting hypernym–hyponym relations for Chinese taxonomy learning

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Abstract

Hypernym–hyponym (“is-a”) relations are key components in taxonomies, object hierarchies and knowledge graphs. Robustly harvesting of such relations requires the analysis of the linguistic characteristics of is-a word pairs in the target language. While there is abundant research on is-a relation extraction in English, it still remains a challenge to accurately identify such relations from Chinese knowledge sources due to the flexibility of language expression and the significant differences between the two language families. In this paper, we introduce a weakly supervised framework to extract Chinese is-a relations from user-generated categories. It employs piecewise linear projection models trained on an existing Chinese taxonomy built from Wikipedia and an iterative learning algorithm to update model parameters incrementally. A pattern-based relation selection method is proposed to prevent “semantic drift” in the learning process using bi-criteria optimization. Experimental results on the publicly available test set illustrate that the proposed approach outperforms state-of-the-art methods.

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Notes

  1. Baidu Baike (http://baike.baidu.com/) is one of the largest online encyclopedia websites in China. The example is taken from the online version Baidu Baike in June, 2016.

  2. http://www.ltp-cloud.com/download/

  3. In practice, there can be over two candidate hyponyms in “Such-As” and “Co-Hyponym” patterns. For simplicity, we only list two here, denoted as \(x_i\) and \(x_j\).

  4. http://nlpchina.github.io/ansj_seg/.

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Acknowledgements

We thank anonymous reviewers for their very useful comments and suggestions. This work is supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000904. Chengyu Wang is partially supported by the ECNU Outstanding Doctoral Dissertation Cultivation Plan of Action under Grant No. YB2016040. This manuscript is an extended version of the paper “Chinese Hypernym-Hyponym Extraction from User Generated Categories” presented at COLING 2016 [30]. The Chinese taxonomy construction technique is based on our previous work, which was presented at APWeb 2015, entitled “User Generated Content Oriented Chinese Taxonomy Construction” [18].

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Authors and Affiliations

  1. School of Computer Science and Software Engineering, East China Normal University, Shanghai, 200062, China

    Chengyu Wang, Yan Fan & Xiaofeng He

  2. School of Data Science and Engineering, East China Normal University, Shanghai, 200062, China

    Aoying Zhou

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  1. Chengyu Wang
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  2. Yan Fan
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Correspondence to Xiaofeng He.

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Wang, C., Fan, Y., He, X. et al. Predicting hypernym–hyponym relations for Chinese taxonomy learning. Knowl Inf Syst 58, 585–610 (2019). https://doi.org/10.1007/s10115-018-1166-1

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