Rastreamento de referência nas línguas Sakurabiat e Wayoro: uma análise contrastando cláusulas matrizes e subordinadas
Bibliographic record
Abstract
A interrelação entre identificação de relações gramaticais, alinhamento morfossintático e rastreamento de referências é um campo de estudo ainda pouco investigado para línguas amazônicas. Os principais sistemas de identificação da relação entre sintagmas nominais argumentos e predicados são a ordem de constituintes, o caso nominal e a concordância verbal. Dentre esses sistemas, as línguas Tupi utilizam, em geral, uma combinação de ordem de constituintes e concordância/indexação verbal. Este estudo envolve línguas do ramo Tupari (Tupi), caracterizado por um sistema de alinhamento híbrido nominativo-absolutivo. Analisaremos dados das línguas Sakurabiat e Wayoro, aplicando a perspectiva tipológico-funcional (HASPELMATH, 2011; SHOPEN, 2007) para avançar na descrição do(s) sistema(s) de alinhamento, com foco especial na análise do rastreamento de referência na estrutura informacional. A análise de relações anafóricas e de controle entre cláusulas principais e subordinadas indica que os argumentos S/A funcionam como pivôs para o controle e identificação de referência.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".