Delayed structural prediction for relative clauses: A new argument for learning to parse from Santiago Laxopa Zapotec

Comprehenders in many of the world’s languages exhibit a preference or a greater ease in comprehending transitive relative clauses (RCs) when associating the dislocated head with a subject position. Some theories relate this preference to an early prediction that an animate head will serve as a subject. We present a picture selection experiment with eye-tracking investigating the role of such predictions in comprehending transitive RCs in Santiago Laxopa Zapotec, an Oto-Manguean language of southern Mexico where RCs are ambiguous unless they contain a resumptive pronoun. Patterns of offline choices and incremental looking suggest that Santiago Laxopa Zapotec comprehenders avoid forming predictive interpretations of the RC head, and do not take its animacy into account in early processing. Instead, comprehenders exhibit a later, animacy-sensitive bias to interpret the RC-internal co-argument as a subject. Overall, we take this pattern as evidence that a comprehender’s structural predictions must be somehow dependent on experience-based tuning, while more universal pressures like similarity-based interference remain fixed. The lingering question for theories of cross-linguistic processing is how much of our predictive mechanism is tunable: do we tune just the distribution of expected structures which directs predictions, or also the practice of deploying predictions itself? We discuss how either of these approaches might explain the pattern we observe in Santiago Laxopa Zapotec, and highlight that an answer to this question will depend on continued investigations across a diverse sample of the world’s languages.

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Journal
Cognition
Published
2026-06-13
DOI
https://doi.org/10.1016/j.cognition.2026.106599
Primary Topic
Categorization, perception, and language
Type
article
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article

Delayed structural prediction for relative clauses: A new argument for learning to parse from Santiago Laxopa Zapotec

Matthew Wagers, John Duff, Maziar Toosarvandani, Delaney Gomez-Jackson et al.
Cognition
Categorization, perception, and language
article

Delayed structural prediction for relative clauses: A new argument for learning to parse from Santiago Laxopa Zapotec

Matthew Wagers, John Duff, Maziar Toosarvandani, Delaney Gomez-Jackson, Fe Silva Robles
article en

Abstract

Comprehenders in many of the world’s languages exhibit a preference or a greater ease in comprehending transitive relative clauses (RCs) when associating the dislocated head with a subject position. Some theories relate this preference to an early prediction that an animate head will serve as a subject. We present a picture selection experiment with eye-tracking investigating the role of such predictions in comprehending transitive RCs in Santiago Laxopa Zapotec, an Oto-Manguean language of southern Mexico where RCs are ambiguous unless they contain a resumptive pronoun. Patterns of offline choices and incremental looking suggest that Santiago Laxopa Zapotec comprehenders avoid forming predictive interpretations of the RC head, and do not take its animacy into account in early processing. Instead, comprehenders exhibit a later, animacy-sensitive bias to interpret the RC-internal co-argument as a subject. Overall, we take this pattern as evidence that a comprehender’s structural predictions must be somehow dependent on experience-based tuning, while more universal pressures like similarity-based interference remain fixed. The lingering question for theories of cross-linguistic processing is how much of our predictive mechanism is tunable: do we tune just the distribution of expected structures which directs predictions, or also the practice of deploying predictions itself? We discuss how either of these approaches might explain the pattern we observe in Santiago Laxopa Zapotec, and highlight that an answer to this question will depend on continued investigations across a diverse sample of the world’s languages.

CognitionVol. 275
Motorola (United States) (US), Center for Applied Linguistics (US), Motorola (South Korea) (KR), University of California, Santa Cruz (US)
Quality Education
Openalex Percentile: Top 4%
Categorization, perception, and language
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