TextGraphs 2024 Shared Task on Text-Graph Representations for Knowledge Graph Question Answering

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

This paper describes the results of the Knowledge Graph Question Answering (KGQA) shared task that was co-located with the TextGraphs 2024 workshop. In this task, given a textual question and a list of entities with the corresponding KG subgraphs, the participating system should choose the entity that correctly answers the question. Our competition attracted thirty teams, four of which outperformed our strong ChatGPT-based zero-shot baseline. In this paper, we overview the participating systems and analyze their performance according to a large-scale automatic evaluation. To the best of our knowledge, this is the first competition aimed at the KGQA problem using the interaction between large language models (LLMs) and knowledge graphs.
Originalspracheundefiniert/unbekannt
TitelProceedings of TextGraphs-17: Graph-based Methods for Natural Language Processing
HerausgeberDmitry Ustalov, Yanjun Gao, Alexander Pachenko, Elena Tutubalina, Irina Nikishina, Arti Ramesh, Andrey Sakhovskiy, Ricardo Usbeck, Gerald Penn, Marco Valentino
Anzahl der Seiten10
ErscheinungsortBangkok, Thailand
VerlagAssociation for Computational Linguistics (ACL)
Erscheinungsdatum01.08.2024
Seiten116-125
PublikationsstatusErschienen - 01.08.2024