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May 8, 2026Transactions of the Association for Computational Linguistics0 citationsOpen Access

Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP Research

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MPMolly R. PetersenCSClaire E. StevensonLPLonneke van der Plas

Key Points

  • This research aims to connect analogical reasoning theories from cognitive science with challenges in natural language processing.
  • Summarized key theories of analogical reasoning from cognitive science literature.
  • Related these theories to current challenges in natural language processing.
  • Identified implications for optimizing relational understanding in text over entity-level similarity.
  • Demonstrated the relevance of cognitive processes to challenges not directly tied to analogy solving in NLP.
  • Provided insights that may help improve relational understanding in textual data.

Abstract

Abstract Analogical reasoning is an essential aspect of human cognition. In this paper, we summarize key theories about the processes underlying analogical reasoning from the cognitive science literature and relate it to current research in natural language processing. While these processes can be easily linked to concepts in NLP, they are generally not viewed through a cognitive lens. Furthermore, we show how these notions are relevant for several major challenges in NLP research, not directly related to analogy solving. This may guide researchers to better optimize relational understanding in text, as opposed to relying heavily on entity-level similarity.

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Cite This Study

Petersen et al. (2026) studied this question.

synapsesocial.com/papers/69fd7f65bfa21ec5bbf07f85https://doi.org/10.1162/tacl.a.632
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