TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866912354835365888 |
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| author | Dorkin, Aleksei Sirts, Kairit |
| author_facet | Dorkin, Aleksei Sirts, Kairit |
| contents | We present our submission to the Task 5 of SemEval-2025 that aims to aid librarians in assigning subject tags to the library records by producing a list of likely relevant tags for a given document. We frame the task as an information retrieval problem, where the document content is used to retrieve subject tags from a large subject taxonomy. We leverage two types of encoder models to build a two-stage information retrieval system -- a bi-encoder for coarse-grained candidate extraction at the first stage, and a cross-encoder for fine-grained re-ranking at the second stage. This approach proved effective, demonstrating significant improvements in recall compared to single-stage methods and showing competitive results according to qualitative evaluation. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_21547 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval Dorkin, Aleksei Sirts, Kairit Computation and Language We present our submission to the Task 5 of SemEval-2025 that aims to aid librarians in assigning subject tags to the library records by producing a list of likely relevant tags for a given document. We frame the task as an information retrieval problem, where the document content is used to retrieve subject tags from a large subject taxonomy. We leverage two types of encoder models to build a two-stage information retrieval system -- a bi-encoder for coarse-grained candidate extraction at the first stage, and a cross-encoder for fine-grained re-ranking at the second stage. This approach proved effective, demonstrating significant improvements in recall compared to single-stage methods and showing competitive results according to qualitative evaluation. |
| title | TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2504.21547 |