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Record W2056258147 · doi:10.1142/s0218213005002028

APPLICATIVE AND COMBINATORY CATEGORIAL GRAMMAR AND SUBORDINATE CONSTRUCTIONS IN FRENCH

2005· article· en· W2056258147 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Artificial Intelligence Tools · 2005
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsCombinatory categorial grammarCategorial grammarCombinatory logicComputer scienceCognitive grammarInterrogativeLinguisticsLink grammarGeneralizationGrammarMildly context-sensitive grammar formalismEmergent grammarHead-driven phrase structure grammarGenerative grammarNatural language processingArtificial intelligenceCognitionProgramming languageMathematicsPsychology

Abstract

fetched live from OpenAlex

In this article we will present a classification and an analysis, by means of Applicative and Combinatory Categorial Grammar (ACCG), of relative, completive and indirect interrogative propositions in French introduced by "que" and "qui". Applicative and Combinatory Categorial Grammar is a generalization of standard Categorial Grammar. It is represented by a canonical association between Steedman's Combinatory Categorial rules and Curry's combinators. This model is included in the general framework of Applicative and Cognitive Grammar with three levels of representation: (i) phenotype (concatened expressions); (ii) genotype (applicative expressions); (iii) the cognitive representations (meaning of linguistic predicates). We are interested only in phenotype and genotype levels.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.395

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.314
Teacher spread0.289 · 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