Probabilistic Modeling of Discourse‐Aware Sentence Processing. (24th April 2013)

• Record Type: Journal Article
• Authors: Dubey, Amit; Keller, Frank; Sturt, Patrick
• Is Part Of: Topics in cognitive science. Volume 5:Number 3(2013:Jul.)
• Page Start: 425
• Page End: 451
• Publication Date: 2013-04-24
• Subjects: Cognitive modeling -- Sentence processing -- Discourse/syntax interactions -- Co‐reference resolution -- Markov logic; Cognitive science -- Periodicals; Cognitive Science -- Periodicals; 153.05
• DOI: 10.1111/tops.12023
• Languages: English
• ISSNs: 1756-8757

Abstract

Abstract: Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co‐reference. The novel combination of probabilistic syntactic components with co‐reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad‐coverage reading‐time corpus.