DICIONÁRIO MULTILÍNGUE DO MEIO AMBIENTE: TERMOS EM PORTUGUÊS BRASILEIRO
Bibliographic record
Abstract
DICIONÁRIO MULTILÍNGUE DO MEIO AMBIENTE: TERMOS EM PORTUGUÊS BRASILEIROResumo: No presente artigo, apresentamos uma pesquisa conduzida para a elaboração do dicionário multilíngue do meio ambiente, com termos em português brasileiro, em colaboração com o Dictionnaire fondamental de l’environnment (DiCoEnviro) desenvolvido pelo Observatoire de Linguistique SensTexte (OLST) da Université de Montréal, no Canadá. A partir de modelos léxico-semânticos aplicados à terminologia, com base em L’Homme (2004, 2015, 2016), e a semântica de frames com base no projeto FrameNet (2015), a pesquisa foi conduzida, e está em andamento, com a finalidade de selecionar termos e identificar as suas relações terminológicas, assim como de descrever as propriedades linguísticas dos termos e conectar tal descrição a uma representação conceitual a partir da delimitação de frames.Palavras-chave: terminologia; semântica lexical; semântica de frames; meio ambiente. MULTILINGUAL DICTIONARY OF THE ENVIRONMENT: TERMS IN BRAZILIAN PORTUGUESEAbstract: This article presents a research carried out to prepare a multilingual dictionary on the environment with terms in Brazilian Portuguese. This project works in collaboration with the Dictionnaire fondamental de l’environnment (DiCoEnviro) developped by the Observatoire de Linguistique SensTexte (OLST) at the Université de Montréal in Canada. Based on lexical semantic approaches applied to Terminology drawing on L’Homme (2004, 2015, 2016) and frame semantics, mainly the FrameNet project (2015), the research has been conducted with the purpose of selecting terms and identifying their terminological relationships at the same time that it describes the linguistic properties of terms and connects this description to conceptual representations based on frames.Keywords: terminology; lexical semantics; frame semantics; environment. DICCIONARIO MULTILÍNGÜE DEL MEDIO AMBIENTE: TÉRMINOS EN PORTUGUÉS BRASILEÑOResumen: En este artículo, presentamos un estudio llevado a cabo para la preparación de diccionario multilingüe del medio ambiente, con términos en portugués brasileño, en colaboración con el Dictionnaire fondamental de l'environnement (DiCoEnviro) desarrollado por el Observatoire de Linguistique Sens-Texte (OLST) de la Université de Montréal, en Canadá. A partir de modelos léxicosemánticos aplicados a la terminología, con base en L'Homme (2004, 2015, 2016), y la semántica de frames con base en el proyecto FrameNet (2015), la investigación fue conducida, y está en marcha, con la finalidad de seleccionar términos e identificar sus relaciones terminológicas, así como de describir las propiedades lingüísticas de los términos y conectar dicha descripción a una representación conceptual a partir de la delimitación de frames.Palabras clave: terminologia; semántica lexical; semántica de frames; medio ambiente.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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; both teacher heads agree on what is shown here.
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".