Vers une modélisation lexicographique des propriétés sémantico-pragmatiques des locutions-phrases génériques et situationnelles La nuit porte conseil et Le chat est sorti du sac
Bibliographic record
Abstract
This article focuses on two categories of ready-made phrases, called generic idiomatic phrases and situational idiomatic phrases. In summary, these sentences are characterized as follows: – they are presented, by the speaker/writer, as descriptions of the world; – they refer or purport to refer to states of fact (although they may implicitly perform illocutionary expressive and/or directive acts); – they acquire their legitimacy according to the discursive theme. The aim is to propose a lexicographical modelling for the kinds of sentences studied. The proposals are inspired by the methodology underlying the elaboration of definitions in the Explanatory and Combinatorial Dictionary (Mel'čuk et al., 1984, 1988, 1992, 1999). Briefly, the semantic-pragmatic analysis scheme sketched reflects 1) the conventional meaning (codified in language) associated with the phrases studied, and 2) the meaning possibly communicated through a generalized implicature (Grice, 1979 [1975]). Close attention is paid to the actions performed by language, which is an inescapable matter whenever statements are involved. The study ends with the presentation of dictionary articles prepared for the generic idiomatic phrase La nuit porte conseil and for the situational idiomatic phrase Le chat est sorti du sac.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".