Classification of verb morphology in Sangesari: insights into the grammatical patterns of an endangered language
Bibliographic record
Abstract
This study presents a paradigmatic description of the Sangesari verbal system, and explores the implications for language learning. Phonological features including consonants, vowels, syllable structure, and stress patterns are briefly described. Syntactic categories, such as nouns, pronouns, adjectives, and adverbs, are also discussed. The research reveals three paradigm classes for the past tense and a single paradigm for the present tense within the Sangesari verb system. Moreover, it highlights markings for phi-features, tense (present and nonpresent), aspect (progressive, perfect, double-perfect and imperfect), and mode, providing insight into Sangesari verb morphology. Based on these findings, recommendations are provided for effective language learning. Learners are encouraged to focus on mastering the complex verb morphology of Sangesari through practices such as verb stem formation, recognition of tense and aspect features, and contextual usage. By focusing on verb structure, learners can build a strong foundation for proficiency in Sangesari.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".