Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Tagging

Hadi Bayrami Asl Tekanlou, Jafar Razmara, Mahsa Sanaei, Mostafa Rahgouy, Hamed Babaei Giglou
4/30/2025
cs.CLcs.AI

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Abstract

This paper presents our system, Homa, for SemEval-2025 Task 5: Subject Tagging, which focuses on automatically assigning subject labels to technical records from TIBKAT using the Gemeinsame Normdatei (GND) taxonomy. We leverage OntoAligner, a modular ontology alignment toolkit, to address this task by integrating retrieval-augmented generation (RAG) techniques. Our approach formulates the subject tagging problem as an alignment task, where records are matched to GND categories based on semantic similarity. We evaluate OntoAligner's adaptability for subject indexing and analyze its effectiveness in handling multilingual records. Experimental results demonstrate the strengths and limitations of this method, highlighting the potential of alignment techniques for improving subject tagging in digital libraries.

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Cite this paper

@article{tekanlou2025homa,
  title  = {Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Tagging},
  author = {Hadi Bayrami Asl Tekanlou and Jafar Razmara and Mahsa Sanaei and Mostafa Rahgouy and Hamed Babaei Giglou},
  year   = {2025},
  eprint = {2504.21474},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.21474v1}
}

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