Methods for Recognizing Nested Terms

In this paper, we describe our participation in the RuTermEval competition devoted to extracting nested terms.We apply the Binder model, which was previously successfully applied to the recognition of nested named entities, to extract nested terms.We obtained the best results of term recognition in all three tracks of the RuTermEval competition.In addition, we study the new task of recognition of nested terms from flat training data annotated with terms without nestedness.We can conclude that several approaches we proposed in this work are viable enough to retrieve nested terms effectively without nested labeling of them.

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Publication Details

Journal
Computational Linguistics and Intellectual Technologies
Published
2025-01-01
DOI
https://doi.org/10.28995/2075-7182-2025-23-299-311
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Methods for Recognizing Nested Terms

Natalia Loukachevitch, І. М. Рожков
Computational Linguistics and Intellectual Technologies
Natural Language Processing Techniques
article

Methods for Recognizing Nested Terms

Natalia Loukachevitch, І. М. Рожков
article en

Abstract

In this paper, we describe our participation in the RuTermEval competition devoted to extracting nested terms.We apply the Binder model, which was previously successfully applied to the recognition of nested named entities, to extract nested terms.We obtained the best results of term recognition in all three tracks of the RuTermEval competition.In addition, we study the new task of recognition of nested terms from flat training data annotated with terms without nestedness.We can conclude that several approaches we proposed in this work are viable enough to retrieve nested terms effectively without nested labeling of them.

Computational Linguistics and Intellectual Technologies
Openalex Percentile: Top 88%
Natural Language Processing Techniques
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