The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval
Alam, Firoj Struss, Julia Maria Chakraborty, Tanmoy Dietze, Stefan Hafid, Salim Korre, Katerina Muti, Arianna Nakov, Preslav Ruggeri, Federico Schellhammer, Sebastian
Alam, Firoj
Struss, Julia Maria
Chakraborty, Tanmoy
Dietze, Stefan
Hafid, Salim
Korre, Katerina
Muti, Arianna
Nakov, Preslav
Ruggeri, Federico
Schellhammer, Sebastian
Supervisor
Department
Natural Language Processing
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
The CheckThat! lab aims to advance the development of innovative technologies designed to identify and to counteract online disinformation and manipulation efforts across various languages and platforms. The first five editions of the CheckThat! lab focused on the main tasks of the information verification pipeline: check-worthiness, evidence retrieval and pairing, and verification. Since the 2023 edition, the lab has broadened the focus and addressed new problems on auxiliary tasks supporting research and decision-making during the verification process. In the 2025 edition of the lab, we consider tasks at the core of the verification pipeline again as well as auxiliary tasks: Task 1 is on identification of subjectivity (a follow up of the CheckThat! 2024 edition), Task 2 is on claim normalization, Task 3 addresses fact-checking numerical claims, and Task 4 focuses on scientific web discourse processing. These tasks represent challenging classification and retrieval problems at the document and at the span level, including multilingual settings.
Citation
F. Alam et al., “The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval,” Lecture Notes in Computer Science, vol. 15576 LNCS, pp. 467–478, 2025, doi: 10.1007/978-3-031-88720-8_68/TABLES/3
Source
Lecture Notes in Computer Science
Conference
47th European Conference on Information Retrieval, ECIR 2025
Keywords
authority finding, disinformation, fact-checking, factuality, model robustness, political bias, subjectivity
Subjects
Source
47th European Conference on Information Retrieval, ECIR 2025
Publisher
Springer Nature