A Method for Constructing Open-Domain Chinese Entity Hypernym Hierarchical Structure

doi:10.3969/j. issn.1673-5188.2017.01.008

ZTE Communications ›› 2017, Vol. 15 ›› Issue (1): 49-54.doi: 10.3969/j. issn.1673-5188.2017.01.008

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A Method for Constructing Open-Domain Chinese Entity Hypernym Hierarchical Structure

CAI Hongbo¹, CHEN Hong², LIU Shen¹

1.Harbin Institute of Technology, Harbin 150001, China
2.ZTE Corporation, Nanjing 210012, China

Received:2015-11-05 Online:2017-02-25 Published:2019-12-24
About author:CAI Hongbo (hbcai@ir.hit.edu.cn) received his master’s degree from School of Computer Science and Technology, Harbin Institute of Technology, China. He is an engineer at Alibaba Corporation. His main research interest is entity relation graphs.|CHEN Hong (chen.hong3@zte.com.cn) received her B.S. degree from the Department of Information Engineering, Nangjing University of Posts and Telecommunications, China in 2007. She is a senior research engineer at ZTE Corporation. Her research interests incloud social network analysis and intelligent question answering. She holds five patents .|LIU Shen (sliu@ir.hit.edu.cn) received his master’s degree from School of Computer Science and Technology, Harbin Institute of Technology, China. He is an engineer at Miaozhen System. His main research interest is entity relation extraction.
Supported by:
This work was supported by ZTE Industry-Academia-Research Cooperation Funds

Abstract

Abstract:

Entity relation is an essential component of some famous knowledge bases, such as Freebase, Yago and Knowledge Graph, while the hyponymy plays an important role in entity relations that show the relationship between the more general terms (hypernyms) and the more specific instances of the terms (hyponyms). In this paper, we present a comprehensive scheme of open-domain Chinese entity hypernym hierarchical construction. Some of the most important unsupervised and heuristic approaches for building hierarchical structure are covered in sufficient detail along with reasonable analyses. We experimentally evaluate the proposed methods and compare them with other baselines. The result shows high precision of our method and the proposed scheme will be further improved with larger scale corpora.

Key words: Entity hypernym, hierarchization, Apriori Algorithm, suffix hypernym, open-domain

CAI Hongbo, CHEN Hong, LIU Shen. A Method for Constructing Open-Domain Chinese Entity Hypernym Hierarchical Structure[J]. ZTE Communications, 2017, 15(1): 49-54.

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Entity	Hypernym
百金花 (centaury)	植物 (plant)
百金花 (centaury)	花 (flower)
百金花 (centaury)	中药 (traditional Chinese medicine)
日本角鲨 (Squalus japonicus)	生物 (living thing)
日本角鲨 (Squalus japonicus)	动物 (animal)
黄色白茧蜂 (Phanerotoma flava Ashmead)	昆虫 (insect)

Hypernym A	The hypernym of A	Confidence	Support
川菜 (Sichuan Cuisine)	饮食 (diet)	1	38
石竹亚纲 (Caryophyllidae)	植物 (plant)	0.968994	64
种子植物门 (Spermatophyta)	植物 (plant)	0.977477	1501
石竹目 (Caryophyllales)	种子植物门 (Spermatophyta)	1	63
鸟类 (bird)	动物 (animal)	1	58
冬青属 (ilex L.)	双子叶植物纲 (Dicotyledoneae)	0.907029	21

Variables and functions	Definition
Confidence (A, B)	The probability that B is one hypernym of A for pre-estimation accuracy.
Support (A, B)	The statistical support that B is one hypernym of A.
Count (A, B)	The number of times A and B co-occur in the same entity hypernym set.
Count (A)	The number of times A occurs in all the entity hypernym set.

Parameter	Definition	Value
C₁	Forward direction confidence	0.9
C₂	Backward direction confidence	0.8
S₁	Minimum support	5
S₂	Basic support	10

	Precision	The relation number (no indirect edge)	Percentage of number increase
No optimization	97.0% (±1%)	3396	-
Linear optimization	97.0% (±1%)	5422	60.00%
Logarithmic optimization	84.5% (±1%)	4073	19.90%

A Method for Constructing Open-Domain Chinese Entity Hypernym Hierarchical Structure

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