Judge, Generator, Executioner: Utilizing an LLM for KBC
Clay, A., Jiménez-Ruiz, E. 
ORCID: 0000-0002-9083-4599 & Madhyastha, P. ORCID: 0000-0002-4438-8161 (2025).
Judge, Generator, Executioner: Utilizing an LLM for KBC.
In:
Joint Proceedings of the 3rd Workshop on Knowledge Base Construction from Pre-Trained Language Models and the 4th Challenge on Language Models for Knowledge Base Construction.
3rd Workshop on Knowledge Base Construction from Pre-Trained Language Models and the 4th Challenge on Language Models for Knowledge Base Construction, 2 Nov 2025, Nara, Japan.
Abstract
In this work, we introduce our submission to the 2025 LM-KBC Challenge. In keeping with the spirit of the challenge, we avoided using additional tools or information; to explore the degree to which the LLM was able to holistically handle the task of triple completion. We found that candidate filtering is crucial to refining the quality of the generated triples, as all filters we introduced improved on our baseline. This is further improved upon with the addition of more initial tail candidates per triple, which highlights the LLM’s potential to act as both the generator of candidates and judge of quality in triple completion tasks.
| Publication Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | © 2025 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments: | School of Science & Technology School of Science & Technology > Department of Computer Science |
| SWORD Depositor: |
Available under License Creative Commons Attribution.
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