Bootstrapping a Neural Morphological Analyzer for St. Lawrence Island Yupik from a Finite-State Transducer
Bibliographic record
Abstract
Morphological analysis is a critical enabling technology for polysynthetic languages. We present a neural morphological analyzer for case-inflected nouns in St. Lawrence Island Yupik, an endangered polysythetic language in the Inuit-Yupik language family, treating morphological analysis as a recurrent neural sequence-to-sequence task. By utilizing an existing finite-state morphological analyzer to create training data, we improve analysis coverage on attested Yupik word types from approximately 75% for the existing finite-state analyzer to 100% for the neural analyzer. At the same time, we achieve a substantially higher level of accuracy on a held-out testing set, from 78.9% accuracy for the finite-state analyzer to 92.2% accuracy for our neural analyzer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".