Modeling the Type Hierarchy in High-Dimensional Box Space for Fine-Grained Entity Typing

被引:0
|
作者
Qin, Yixiu [1 ]
Wang, Feng [1 ]
Li, Jiawei [1 ]
Deng, Yuanfei [1 ]
Mao, Shun [1 ]
Jiang, Yuncheng [1 ,2 ]
机构
[1] South China Normal Univ, Sch Comp Sci, Guangzhou 510631, Peoples R China
[2] South China Normal Univ, Sch Artificial Intelligence, Foshan 528225, Peoples R China
来源
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS | 2024年
基金
中国国家自然科学基金;
关键词
Noise; Vectors; Noise measurement; Noise reduction; Computational modeling; Organizations; Named entity recognition; Graph neural networks; Electronic mail; Context modeling; Fine-grained entity typing; high-dimensional box embeddings; information extraction; type hierarchy;
D O I
10.1109/TCSS.2024.3515054
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A critical component of fine-grained entity typing is the existence of precise relationship between entity types, such as type hierarchy. Previous approaches for fine-grained entity typing typically model the type hierarchy in vector space, which causes it extremely hard to precisely capture the complex relationship between entity types. To overcome the challenge of modeling type hierarchy in vector space, this article proposes for the first time to model the type hierarchy in high-dimensional box space. In addition, previous approaches focus more on the influence of the context of entity mentions, while neglecting the influence of entity mentions themselves. Based on the above challenges, we present a new approach called THBox, which not only successfully boosts the influence of entity mentions but also models the type hierarchy well. To verify the effectiveness of the method presented in this article, experimental results on three publicly available fine-grained entity typing benchmark datasets are provided to verify that the presented method is a new state-of-the-art solution for fine-grained entity typing.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Fine-Grained Entity Typing in Hyperbolic Space
    Lopez, Federico
    Heinzerling, Benjamin
    Strube, Michael
    4TH WORKSHOP ON REPRESENTATION LEARNING FOR NLP (REPL4NLP-2019), 2019, : 169 - 180
  • [2] Improved Box Embeddings for Fine-Grained Entity Typing
    Qin, Yixiu
    Wang, Yizhao
    Li, Jiawei
    Mao, Shun
    Wang, He
    Jiang, Yuncheng
    IEEE TRANSACTIONS ON BIG DATA, 2023, 9 (06) : 1631 - 1642
  • [3] Chinese Fine-Grained Entity Typing Based on Box Embedding
    Liu, Pan
    Guo, Yanming
    Lei, Jun
    Li, Guohui
    2024 10TH INTERNATIONAL CONFERENCE ON BIG DATA AND INFORMATION ANALYTICS, BIGDIA 2024, 2024, : 241 - 246
  • [4] Modeling Fine-Grained Entity Types with Box Embeddings
    Onoe, Yasumasa
    Boratko, Michael
    McCallum, Andrew
    Durrett, Greg
    59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 1 (ACL-IJCNLP 2021), 2021, : 2051 - 2064
  • [5] Multilingual Fine-Grained Entity Typing
    van Erp, Marieke
    Vossen, Piek
    LANGUAGE, DATA, AND KNOWLEDGE, LDK 2017, 2017, 10318 : 262 - 275
  • [6] Fine-Grained Entity Typing With a Type Taxonomy: A Systematic Review
    Wang, Ruili
    Hou, Feng
    Cahan, Steven F.
    Chen, Li
    Jia, Xiaoyun
    Ji, Wanting
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 35 (05) : 4794 - 4812
  • [7] Improving Fine-grained Entity Typing with Entity Linking
    Dai, Hongliang
    Du, Donghong
    Li, Xin
    Song, Yangqiu
    2019 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING AND THE 9TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (EMNLP-IJCNLP 2019): PROCEEDINGS OF THE CONFERENCE, 2019, : 6210 - 6215
  • [8] Fine-Grained Entity Typing with High-Multiplicity Assignments
    Rabinovich, Maxim
    Klein, Dan
    PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 2, 2017, : 330 - 334
  • [9] Transfer learning for fine-grained entity typing
    Hou, Feng
    Wang, Ruili
    Zhou, Yi
    KNOWLEDGE AND INFORMATION SYSTEMS, 2021, 63 (04) : 845 - 866
  • [10] A Chinese Corpus for Fine-grained Entity Typing
    Lee, Chin
    Dai, Hongliang
    Song, Yangqiu
    Li, Xin
    PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020), 2020, : 4451 - 4457