Toward a model of children's story comprehension

By Eugene Charniak. 1972

Subfields: Cognitive Science & Psychology

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Citations in the corpus

A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories (2016, background): “Story understanding is an extremely challenging task in natural language understanding with a long-running history in AI (Charniak, 1972; Winograd, 1972; Turner, 1994; Schubert and Hwang, 2000).”
LSDSem 2017 Shared Task: The Story Cloze Test (2017, background): “Building systems that can understand stories or can compose meaningful stories has been a long-standing ambition in natural language understanding (Charniak, 1972; Winograd, 1972; Turner, 1994; Schubert and Hwang, 2000).”
Coreference Resolution with World Knowledge (2011, background): “The difﬁculty of the task stems in part from its reliance on world knowledge (Charniak, 1972).”
Aiding Pronoun Translation with Co-Reference Resolution (2010, background): “Hobbs also refers to the work by Charniak [1972] and Wilks [1975] for the problem of anaphora resolution.”
Assessing Critical Thinking in the Writing of Japanese University Students (2001, methodology): “An example from Chamiak (1972) illustrates how this works:”
Learning Semantic Parsers: An Important but Under-Studied Problem (2004, background): “1978) and understanding short stories (Charniak 1972; Schank 1975; Charniak & Wilks 1976; Schank & Abelson 1977; Schank & Riesbeck 1981).”
Understanding script-based stories using commonsense reasoning (2004, unknown): “A number of story understanding systems have been built (Charniak, 1972; Cullingford, 1978; Wilensky, 1978; Lebowitz, 1980; Schank and Riesbeck, 1981; Dyer, 1983; Dolan, 1989; Norvig, 1989; Reeves, 1991; Miikkulainen, 1993; Hobbs et al., 1993; Schank, Kass, and Riesbeck, 1994; Shapiro and Rapaport,…”
Supervised Noun Phrase Coreference Research: The First Fifteen Years (2010, background): “Despite its simple task definition, coreference is generally considered a difficult NLP task, typically involving the use of sophisticated knowledge sources and inference procedures (Charniak, 1972).”
Story Comprehension for Predicting What Happens Next (2017, background): “Story comprehension involves not only an array of NLP capabilities, but also some common sense knowledge and an understanding of normative social behavior (Charniak, 1972).”
Scripts, Plans and Knowledge (1975, background): “Charniak (1972) approached the problem from the other end entirely and has made some interesting first steps, but because his work is not grounded in any representational sys tem or any working computational system the res triction of world knowledge need not critically concern him.”
The Intentional Stance. (1987, background): “We could try to list all the "things you needed to know" to get the joke (Charniak 1974).”
Tackling the Story Ending Biases in The Story Cloze Test (2018, background): “Story comprehension has been one of the longestrunning ambitions in artificial intelligence (Dijk, 1980; Charniak, 1972).”