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
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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