The role of input cues in acquiring unaccusative and unergative verbs: Verb learning experiments with Mandarin-speaking toddlers
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Bibliographic record
Abstract
Children make use of various information in linguistic input to learn verbs, including syntactic distribution and semantic features. Within the intransitive verb class, unaccusative and unergative verbs differ in distribution with respect to word order as well as in semantic features such as telicity. Both the distributional and semantic information might act as cues for learning the two types of verbs. In this study, we investigate how Mandarin-speaking toddlers make use of these input cues to learn the unaccusative-unergative distinction. In verb learning experiments using the visual fixation procedure, 31-month-old toddlers were taught two novel verb items (V UA and V UE ) and then tested on whether they were able to distinguish them. Results show that participants learned the difference between the two novel verbs based on the word-order cue and the telicity cue separately, but not simultaneously. Our findings provide evidence for toddlers’ ability to employ distributional and semantic information in the input during verb learning, shedding light on the learning mechanisms of verb argument structure.
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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 | 0.000 |
| Open science | 0.000 | 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 it