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Review
. 2022 May 24:5:796741.
doi: 10.3389/frai.2022.796741. eCollection 2022.

Beyond the Benchmarks: Toward Human-Like Lexical Representations

Suzanne Stevenson  1 , Paola Merlo  2
Affiliations
Review

Beyond the Benchmarks: Toward Human-Like Lexical Representations

Suzanne Stevenson et al. Front Artif Intell. .

Abstract

To process language in a way that is compatible with human expectations in a communicative interaction, we need computational representations of lexical properties that form the basis of human knowledge of words. In this article, we concentrate on word-level semantics. We discuss key concepts and issues that underlie the scientific understanding of the human lexicon: its richly structured semantic representations, their ready and continual adaptability, and their grounding in crosslinguistically valid conceptualization. We assess the state of the art in natural language processing (NLP) in achieving these identified properties, and suggest ways in which the language sciences can inspire new approaches to their computational instantiation.

Keywords: computational linguistics; cross-linguistic generalization; human lexical representations; lexical semantics; lexicon structure; natural language processing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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