How do Antecedent Semantics Influence Pronoun Interpretation? Evidence from Eye Movements
Bibliographic record
Abstract
Pronoun interpretation is often described as relying on a comprehender's mental model of discourse. For example, in some psycholinguistic accounts, interpreting pronouns involves a process of retrieval, whereby a pronoun is resolved by accessing information from its linguistic antecedent. However, linguistic antecedents are neither necessary nor sufficient for interpreting a pronoun, and even when an antecedent has been introduced in earlier discourse, there is little evidence for the retrieval of linguistic form. The current study extends our understanding of pronoun interpretation by examining whether the semantics of antecedent expressions are retrieved from representations of past discourse. Participants were instructed to move displayed objects in a Visual World eye-tracking task. In some cases, the semantics of the antecedent were no longer viable after an instruction was completed (e.g., "Move the house on the left to area 12," where the result was that a different house is now the leftmost one). In this case, retrieving antecedent semantics at the point of hearing a subsequent pronoun ("Now, move it…") should entail a processing penalty. Instead, the results showed that antecedent semantics have no direct effect on interpretation, raising additional questions about the role that retrieval might play in pronoun interpretation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".