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Record W4226194502 · doi:10.16995/glossa.5816

Children’s comprehension of NP embedding

2022· article· en· W4226194502 on OpenAlexafffund
E. Raymond Hall, Ana Teresa Pérez‐Leroux

Bibliographic record

VenueGlossa a journal of general linguistics · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLocative caseLinguisticsReferentNoun phraseComputer scienceComprehensionNatural language processingSentenceSyntaxArtificial intelligenceSemantics (computer science)NounProgramming language

Abstract

fetched live from OpenAlex

How do children learn to interpret structurally complex noun phrases? NPs embedded inside other NPs are not accessible to predication, so that in a sentence with a subject NP containing a PP modifier such as The cup on the table is green or The dog with the bone is blue, the adjectival predicate has scope over the highest but not the embedded nominal referent (Arsenijevic & Hinzen 2012). We used a coloring task to examine children’s comprehension of sentences containing these complex NPs, comparing PP modifiers (locative and comitatives) to coordinated NPs (The cup and the table are green), where both referents are accessible. Three- to five-year-old children were highly accurate with control and coordinate sentences, and performed well with locative PPs, but were not different from chance level for comitative sentences, which many children treated as coordinates. That children differentiate between coordinate and locative sentences provides evidence that children have early access to the syntax-semantics of complex nominals. The contrast between locatives and comitatives suggests that comprehension is not merely guided by subject agreement (since the agreement patterns are the same for both types of PP-modified subjects), and that children still need to learn the lexical semantics of prepositions. Diachronically, languages with comitative modifiers evolve into language with comitative coordination (Haspelmath 2007). Thus, we propose that these error patterns for comitative prepositions can be explained by the assumption that children’s errors align with the direction of systematic language change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.305
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

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Same venueGlossa a journal of general linguisticsSame topicLanguage Development and DisordersFrench-language works237,207