TextGraphs 2024 Shared Task on Text-Graph Representations for Knowledge Graph Question Answering
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of TextGraphs-17: Graph-based Methods for Natural Language Processing : Graph-Based Methods for Natural Language Processing, 62nd Annual Meeting of the Association of Computational Linguistics |
| Editors | Dmitry Ustalov, Yanjun Gao, Alexander Pachenko, Elena Tutubalina, Irina Nikishina, Arti Ramesh, Andrey Sakhovskiy, Ricardo Usbeck, Gerald Penn, Marco Valentino |
| Number of pages | 10 |
| Place of Publication | Kerrville |
| Publisher | Association for Computational Linguistics (ACL) |
| Publication date | 01.08.2024 |
| Pages | 116-125 |
| ISBN (electronic) | 979-8-89176-145-2 |
| Publication status | Published - 01.08.2024 |
| Event | TextGraphs-17: Graph-based Methods for Natural Language Processing - Bangkok, Thailand Duration: 15.08.2024 → 15.08.2024 Conference number: 17 https://sites.google.com/view/textgraphs2024 |
Bibliographical note
Publisher Copyright:
© 2024 Association for Computational Linguistics.
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