PUB - Publikationen an der Universität Bielefeld

# Towards a model of predictive processing of Implicit Causality Implicit Causality (IC) verbs constitute a central topic in research on prediction in natural language processing. Selecting for two animate arguments, IC verbs display a strong preference for an explanation focusing on one argument: (1) **Mary** fascinated John because … **she** was very clever. *fascinate*: subject bias (2) Mary congratulated **John** because … **he** won the competition. *congratulate*: object bias The predictive nature of IC is still insufficiently understood, however, as witnessed by the recurring debate on integration vs. focusing/prediction. Key questions include: **What is predicted?** A referent, a particular realization of the referent (*she/Mary*) or a type of explanation [1; 10]? Furthermore, **what triggers the prediction**: lexical semantics or world knowledge [2; 8; 10]? And finally, **what is the processing profile** of IC [3]?

Based on a formal theory of IC [1; 10], results from experimental research [3; 5; 9] and recent models of predictive processing [6; 7], we propose a comprehensive framework for the processing of IC. Crucially, we consider in detail the relation between the nature of what is predicted (the *predictee* [8]) and the properties of particular linguistic expressions such as pronouns that may be taken to (in)validate predictions. Based on previous research, we also evaluate the range of top-down and bottom-up processes: Which linguistic levels are involved and how do they interact? Our study shows that a closer investigation of the relation between predictees and (in)validators of predictions in general may contribute towards a better understanding of – and potentially more precise models of – language-based prediction. ## References 1. Bott, Oliver and Torgrim Solstad (2014): "From verbs to discourse – a novel account of implicit causality". In B. Hemforth, B. Mertins, & C. Fabricius-Hansen (Eds.), *Psycholinguistic approaches to meaning and understanding across languages*, 213–251. Springer. 2. Marcelle Crinean and Alan Garnham (2006): Implicit causality, implicit consequentiality and semantic roles. *Language and Cognitive Processes* **21**(5), 636–648. 3. Alan Garnham, Scarlett Child, and Sam Hutton (2020): Anticipating causes and consequences. *Journal of Memory and Language* **114**, Article 104130. 4. Kamide, Yuki (2008): Anticipatory processes in sentence processing. *Language and Linguistics Compass* **2**(4), 647–670. 5. Koornneef, Arnout W., & Joost van Berkum (2006): On the use of verb-based implicit causality in sentence comprehension: Evidence from self-paced reading and eye tracking. *Journal of Memory and Language* **54**(4), 445–465. 6. Kuperberg, Gina and Florian T. Jaeger (2016): What do we mean by prediction in language comprehension? *Language, Cognition and Neuroscience* **31**(1), 32–59. 7. Pickering, Martin J. and Chiara Gambi (2018): Predicting while comprehending language: A theory and review. *Psychological Bulletin* **144**(10), 1002–1044. 8. Pickering, Martin J. and Asifa Majid (2007): What are implicit causality and consequentiality? *Language and Cognitive Processes* **22**(5), 780–788. 9. Pyykkönen, Pirita and Juhani Järvikivi (2010): Activation and persistence of implicit causality information in spoken language comprehension. *Experimental Psychology* **57**(1), 5–16. 10. Solstad, Torgrim and Oliver Bott (2022): On the nature of implicit causality and consequentiality: the case of psychological verbs. *Language, Cognition and Neuroscience* **37**(10), 1311–1340