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Record W2017877614 · doi:10.1017/s0959269507003018

Thematic indirect objects in French

2007· article· en· W2017877614 on OpenAlexaff
Yves Roberge, Michelle Troberg

Bibliographic record

VenueJournal of French Language Studies · 2007
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransitive relationArgument (complex analysis)Object (grammar)Event (particle physics)Computer scienceLinguisticsCausativeThematic mapPosition (finance)Artificial intelligenceMathematicsPhilosophyVerbCombinatoricsPhysicsGeography

Abstract

fetched live from OpenAlex

We present a descriptive generalisation according to which a verbal or an event argument is merged as an indirect object (IO) when the direct object (DO) position is occupied. Our goal is to formalise this generalisation and to show how current syntactic theory provides the necessary tools to support it. Specifically, the converging consensus that all so-called intransitive verbs have an internal nominal argument resolves previous exceptions to the generalisation and shows that the transitivity restriction on thematic IOs is structural.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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 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

Citations12
Published2007
Admission routes1
Has abstractyes

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Same venueJournal of French Language StudiesSame topicNatural Language Processing TechniquesFrench-language works237,207