Thinking About Multiword Constructions: Usage‐Based Approaches to Acquisition and Processing
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Usage‐based approaches to language hold that we learn multiword expressions as patterns of language from language usage, and that knowledge of these patterns underlies fluent language processing. This paper explores these claims by focusing upon verb–argument constructions (VACs) such as “V(erb) about n(oun phrase).” These are productive constructions that bind syntax, lexis, and semantics. It presents (a) analyses of usage patterns of English VACs in terms of their grammatical form, semantics, lexical constituency, and distribution patterns in large corpora; (b) patterns of VAC usage in child‐directed speech and child language acquisition; and (c) investigations of VAC free‐association and psycholinguistic studies of online processing. We conclude that VACs are highly patterned in usage, that this patterning drives language acquisition, and that language processing is sensitive to the forms of the syntagmatic construction and their distributional statistics, the contingency of their association with meaning, and spreading activation and prototypicality effects in semantic reference. Language users have rich implicit knowledge of the statistics of multiword sequences.
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Only in the last few years has it become possible to bring together cognition, corpora, and computing at scale to triangulate research in usage-based language learning.
“Only in the last few years has it become possible to bring together cognition, corpora, and computing at scale to triangulate research in usagebased language learning (N.C. Ellis, 2017).”
From Effects of Availability, Contingency, and Formulaicity on the Accuracy of English Grammatical Morphemes in Second Language Writing (2022) · cites this paper as N.C. Ellis, 2017
The Introduction brings together corpus-linguistic, psychological, and psycholinguistic evidence for usage-based accounts, and Section 2 describes analysis of a 100-million-word corpus. The paper does not say that combining cognition, corpora, and computing at scale became possible only in the last few years; that timing claim is unsupported. (LLM, conf=0.83)
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Murakami, A., & Ellis, N. C. (2022) · Language Learning · doi:10.1111/lang.12500 · Cited by 26 · see citing works
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- Authors
- Ellis, N. C., & Ogden, D. C.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Ellis, Nick C.
- ORCID
- Ellis, Nick C.
- Venue
- Topics in Cognitive Science
- Publisher
- Wiley
- Published
- 2017-02-24
- Volume
- 9
- Issue
- 3
- Pages
- 604-620
- ISSN
- 1756-8757 (ISSN-L)
- 1756-8765
- OpenAlex
- W2589432993
- Cited by
- 66
- References
- 5
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 19 · 2023: 8 · 2022: 11 · 2021: 1 · 2020: 6 · 2019: 6 · 2017: 5 · 2016: 1
- FWCI
- 9.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Topics in Cognitive Science (publishedVersion)
- PubMed (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Keywords
- usage-based linguistics, language acquisition, language processing, child-directed speech, distributional statistics, spreading activation, prototypicality, free association, online processing, semantic reference
- MeSH terms
- Humans, Language, Language Development, Learning, Psycholinguistics, Semantics
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