Tracing knowledge graph provenance from textual knowledge sources

Informazioni relative al progetto

KG-PROVENANCE

ID dell’accordo di sovvenzione: 101146515

DOI

10.3030/101146515

Progetto chiuso

Data della firma CE 6 Marzo 2024

Data di avvio 1 Aprile 2024

Data di completamento 31 Marzo 2026

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 230 774,40

Coordinato da

AARHUS UNIVERSITET
Denmark

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

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

Pubblicazioni

Conference proceedings (5)

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

Autori: Yuxi Xia; Klim Zaporojets; Benjamin Roth
Pubblicato in: Proceedings of the 21st Conference on Natural Language Processing (KONVENS 2025): Long and Short Papers, Numero Pages 12–26, 2025
Editore: HsH Applied Academics

CYCLE: Cross-Year Contrastive Learning in Entity-Linking

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

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

Autori: Fina Polat; Daniel Daza; Pengyu Zhang; Klim Zaporojets; Paul Groth
Pubblicato in: Proceedings of the 25th International Semantic Web Conference, ISWC 2026, Numero To be confirmed, 2026
Editore: Expected to be Springer Nature; confirm from final record

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

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

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

Autori: Yuxi Xia, Pedro Henrique Luz De Araujo, Klim Zaporojets, Benjamin Roth
Pubblicato in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Editore: 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

Autori: 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
Pubblicato in: Expert Systems with Applications, Numero 298, 2026, ISSN 0957-4174
Editore: Elsevier BV
DOI: 10.48550/ARXIV.2505.18475

Book chapters (1)

Lecture Notes in Computer Science

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