DialogRE$$^{C+}$$: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Xiong, Yiyun; Dai, Mengwei; Li, Fei; Fei, Hao; Li, Bobo; Wu, Shengqiong; Ji, Donghong; Teng, Chong

doi:10.1007/978-3-031-44693-1_18

Lecture Notes in Computer Science

2023

DOI: 10.1007/978-3-031-44693-1_18

|Get access via publisher |Cite

DialogRE$$^{C+}$$: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Yiyun Xiong

Mengwei Dai

Fei Li

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Book3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Overview of the NLPCC 2024 Shared Task 3: Dialogue-Level Coreference Resolution and Relation Extraction

Xiong

et al. 2024

Lecture Notes in Computer Science

Get access via publisher Add to dashboard Cite

Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

Overview of the NLPCC 2024 Shared Task 3: Dialogue-Level Coreference Resolution and Relation Extraction

Xiong

et al. 2024

Lecture Notes in Computer Science

Get access via publisher Add to dashboard Cite

Improving Inference via Rich Path Information for Dialogue Relation Extraction

Zhou

et al. 2024

Lecture Notes in Computer Science

Get access via publisher Add to dashboard Cite

NLPCC2024 Shared Task 3 Technical Report

Sun

2024

Lecture Notes in Computer Science

Get access via publisher Add to dashboard Cite

Scite is an AI-powered research tool that helps researchers better discover and evaluate scientific literature through Smart Citations—a revolutionary system that shows whether articles support, contrast, or simply mention a given claim. Founded in 2018, and now part of Research Solutions, Scite has indexed over 1.3 billion citations and partnered with more than 30 major publishers to provide researchers with unparalleled access to scientific literature. With its Scite Assistant, Smart Citation Index, and advanced search capabilities, the platform addresses critical challenges such as information overload and research reproducibility. Trusted by two million active users worldwide, Scite is reshaping how researchers interact with scholarly content—building ethical, transparent AI tools that support rigorous, copyright-compliant research.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms of Service API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

DialogRE$$^{C+}$$: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Cited by 3 publications

References 24 publications

Overview of the NLPCC 2024 Shared Task 3: Dialogue-Level Coreference Resolution and Relation Extraction

Overview of the NLPCC 2024 Shared Task 3: Dialogue-Level Coreference Resolution and Relation Extraction

Improving Inference via Rich Path Information for Dialogue Relation Extraction

NLPCC2024 Shared Task 3 Technical Report

Contact Info

Product

Resources

About