@inproceedings{bayrami-asl-tekanlou-etal-2025-homa,
title = "{H}oma at {S}em{E}val-2025 Task 5: Aligning Librarian Records with {O}nto{A}ligner for Subject Tagging",
author = "Bayrami Asl Tekanlou, Hadi and
Razmara, Jafar and
Sanaei, Mahsa and
Rahgouy, Mostafa and
Babaei Giglou, Hamed",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.312/",
pages = "2400--2406",
ISBN = "979-8-89176-273-2",
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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<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.</abstract>
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%0 Conference Proceedings
%T Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Tagging
%A Bayrami Asl Tekanlou, Hadi
%A Razmara, Jafar
%A Sanaei, Mahsa
%A Rahgouy, Mostafa
%A Babaei Giglou, Hamed
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F bayrami-asl-tekanlou-etal-2025-homa
%X 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.
%U https://aclanthology.org/2025.semeval-1.312/
%P 2400-2406
Markdown (Informal)
[Homa at SemEval-2025 Task 5: Aligning Librarian Records with OntoAligner for Subject Tagging](https://aclanthology.org/2025.semeval-1.312/) (Bayrami Asl Tekanlou et al., SemEval 2025)
ACL