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Dynamicity Predicts Inferred Temporal Order in Complex Sentences: Evidence from English, German, and Polish
Elena Marx1, Oliwia Iwan1, Eva Wittenberg1
1Department of Cognitive Science, Central European University.
Cognitive Science
|February 14, 2025
Summary
People infer temporal order from language by considering situation dynamics, not just linguistic cues. This finding reveals how event perception influences language comprehension under uncertainty.
Area of Science:
- Cognitive Science
- Psycholinguistics
- Event Cognition
Background:
- Temporal inference from language is crucial for mental models.
- Previous research emphasized linguistic structure and pragmatics.
- The role of situation dynamics in temporal inference remains under-explored.
Purpose of the Study:
- To investigate whether dynamic properties of described situations influence temporal order inferences.
- To examine this influence across different languages and encoding types (lexical vs. grammatical).
Main Methods:
- Three pre-registered studies involving adult participants.
- Use of toys to act out complex situations described by main clause-relative clause structures.
- Cross-linguistic comparison (English, German, Polish).
Main Results:
- Non-dynamic state descriptions were consistently ordered first when paired with dynamic events.
- This pattern held regardless of whether dynamicity was lexically or grammatically encoded.
- Findings were consistent across English, German, and Polish.
Conclusions:
- Situation dynamicity is a key factor in temporal inference from language, especially under uncertainty.
- This research bridges language comprehension and event cognition by highlighting dynamicity.
- The findings underscore the interplay between perception and language processing.
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