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

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.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Computational Social Systems
Published
2024-12-25
DOI
https://doi.org/10.1109/tcss.2024.3515054
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Shun Mao, Yixiu Qin, Yuncheng Jiang, Yuanfei Deng et al.
1 citations
IEEE Transactions on Computational Social Systems
Distributed and Parallel Computing Systems
0.35
article

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

Shun Mao, Yixiu Qin, Yuncheng Jiang, Yuanfei Deng, Jiawei Li, Feng Wang
article en
1 citations

Abstract

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.

IEEE Transactions on Computational Social SystemsVol. 12(4)
South China Normal University (CN)
Openalex Percentile: Top 35%
Distributed and Parallel Computing Systems
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.