Data-Oriented Parsing


A New View on Language and Cognition



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Data-Oriented Parsing (DOP) models of natural language propose that human language perception and production work with representations of concrete language experiences, rather than with abstract grammatical rules. These models operate by decomposing the given representations into fragments and recomposing those pieces to analyze new utterances. DOP is therefore a new way to think of what a native speaker knows when s/he knows a language.


The DOP framework has been applied to other modalities as well, such as music, vision, problem-solving and reasoning. DOP is therefore a candidate to solve Allen Newell`s challenge, the search for a single model that unifies perceptual and cognitive modalities. The VICI Group at the University of Amsterdam attempts to meet this challenge.


Here is a light-hearted view on DOP


An accessible introduction to DOP is a tutorial paper by R. Bod and R. Scha, 1996.


A short tutorial into DOP is Sima`an 2003.


For a state-of-the-art overview, see the DOP edited volume.


An overview of DOP applied to other modalities is here.


Here you can find out about the latest books, projects, events and freely available DOP software.



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