Tracing knowledge graph provenance from textual knowledge sources

Informations projet

KG-PROVENANCE

N° de convention de subvention: 101146515

DOI

10.3030/101146515

Projet clôturé

Date de signature de la CE 6 Mars 2024

Date de début 1 Avril 2024

Date de fin 31 Mars 2026

Financé au titre de

• Marie Skłodowska-Curie Actions (MSCA)

Coût total

Aucune donnée

Contribution de l’UE

€ 230 774,40

Coordonné par

AARHUS UNIVERSITET
Denmark

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cyclefor all data sets that will be collected, processed or generated by the action. It is adocument describing what data will be collected, processed or generated andfollowing what methodology and standards, whether and how this data will beshared and/or made open, and how it will be curated and preserved.

Documents, reports (1)

Communication, Dissemination & Exploitation Plan

The plan describes the planned measures to maximize the impact ofthe project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measuresand public engagement strategy, the aim is to inform and reach out to society andshow the activities performed, and the use and the benefits the project will have forcitizens

Publications

Conference proceedings (5)

Learn to pick the winner: Black-box ensembling for textual and visual question answering

Auteurs: Yuxi Xia; Klim Zaporojets; Benjamin Roth
Publié dans: Proceedings of the 21st Conference on Natural Language Processing (KONVENS 2025): Long and Short Papers, Numéro Pages 12–26, 2025
Éditeur: HsH Applied Academics

CYCLE: Cross-Year Contrastive Learning in Entity-Linking

Auteurs: Pengyu Zhang, Congfeng Cao, Klim Zaporojets, Paul Groth
Publié dans: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024, ISSN 2155-0751
Éditeur: ACM
DOI: 10.48550/ARXIV.2410.09127

Select, Don’t Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection

Auteurs: Fina Polat; Daniel Daza; Pengyu Zhang; Klim Zaporojets; Paul Groth
Publié dans: Proceedings of the 25th International Semantic Web Conference, ISWC 2026, Numéro To be confirmed, 2026
Éditeur: Expected to be Springer Nature; confirm from final record

Analysing zero-shot temporal relation extraction on clinical notes using temporal consistency

Auteurs: Vasiliki Kougia, Anastasiia Sedova, Andreas Joseph Stephan, Klim Zaporojets, Benjamin Roth
Publié dans: Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, 2024
Éditeur: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2406.11486

Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles

Auteurs: Yuxi Xia, Pedro Henrique Luz De Araujo, Klim Zaporojets, Benjamin Roth
Publié dans: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Éditeur: Association for Computational Linguistics
DOI: 10.48550/ARXIV.2501.03991

Peer reviewed articles (1)

A survey of large language models for data challenges in graphs

Auteurs: Mengran Li, Pengyu Zhang, Wenbin Xing, Yijia Zheng, Klim Zaporojets, Junzhou Chen, Ronghui Zhang, Yong Zhang, Siyuan Gong, Jia Hu, Xiaolei Ma, Zhiyuan Liu, Paul Groth, Marcel Worring
Publié dans: Expert Systems with Applications, Numéro 298, 2026, ISSN 0957-4174
Éditeur: Elsevier BV
DOI: 10.48550/ARXIV.2505.18475

Book chapters (1)

Lecture Notes in Computer Science

Auteurs: Pengyu Zhang, Klim Zaporojets, Jie Liu, Jia-Hong Huang, Paul Groth
Publié dans: Lecture Notes in Computer Science, The Semantic Web, 2026, ISSN 0302-9743
Éditeur: Springer Verlag
DOI: 10.48550/ARXIV.2603.16974