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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 OpenAlexaff
Ismaïl Biskri

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.005
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2005
Admission routes1
Has abstractyes

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Same venueInternational Journal of Artificial Intelligence ToolsSame topicNatural Language Processing TechniquesFrench-language works237,207