mlsanityData to 14 Oct 2026

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

arXiv 2504.21474 ↗First posted 30 Apr 2025cs.CL cs.AIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 18 references that are in the map. First posted on arXiv 30 Apr 2025.

Builds on

5 of 18 references.

References · 5

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  3. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 229
  4. 2025SemEval-2025 Task 5: LLMs4Subjects -- LLM-based Automated Subject Tagging for a National Technical Library's Open-Access Catalogcited by 10
  5. 2025OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignmentcited by 8

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Citing papers per year: 2025: 1; 2026: 1.

2 papers.

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  1. 2026OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques
  2. 2026The Science Data Lake: A Unified Open Infrastructure Integrating 293 Million Papers Across Eight Scholarly Sources with Embedding-Based Ontology Alignment ↗
  3. 2024Towards Complex Ontology Alignment using Large Language Models
  4. 2026Beyond Similarity: Task-Aligned Retrieval for Language Models
  5. 2025LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models
  6. 2025OntoAligner Meets Knowledge Graph Embedding Aligners
  7. 2026Quantifying Retriever-Generator Alignment in RAG with Local Explanations
  8. 2025Large Language Models as Oracles for Ontology Alignment