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Record W2501694069 · doi:10.1075/rllt.1.02bur

Variable-behavior Ps and the location of PATH in Old French

2009· book-chapter· en· W2501694069 on OpenAlexaff
Heather Burnett, Mireille Tremblay

Bibliographic record

VenueRomance languages and linguistic theory · 2009
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLocative caseLexiconTransitive relationInterpretation (philosophy)Computer scienceLinguisticsSemantics (computer science)Natural language processingVariation (astronomy)Artificial intelligenceVariable (mathematics)Class (philosophy)VerbLexical semanticsLexical itemMathematicsPhilosophyPhysics

Abstract

fetched live from OpenAlex

This paper investigates the interaction between lexical semantics and syntactic structure in the interpretation of prepositional phrases through a study of the lexical encoding of directionality in prepositions and particles in Old French (OF). OF had a series of locative and directional prepositions that could be used intransitively, where they were interpreted directionally or aspectually. We argue that the different interpretations available to these elements are a result of the syntactic configurations into which they are placed, not a systematic homophony in the lexicon. We first show that, for each element in the class under consideration, its interpretation can be predicted based on its transitivity properties and the type of verb with which it is paired. We then present our analysis of the OF prepositional system, and show how the lexical semantics of individual particles and general rules of composition conspire to create the semantic variation found in our data.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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

Citations46
Published2009
Admission routes1
Has abstractyes

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Same venueRomance languages and linguistic theorySame topicLinguistics and Discourse AnalysisFrench-language works237,207