Parsing with Principles and Classes of Information presents a parser
based on current principle-based linguistic theories for English. It
argues that differences in the kind of information being computed,
whether lexical, structural or syntactic, play a crucial role in the
mapping from grammatical theory to parsing algorithms.
The direct encoding of homogeneous classes of information has
computational and cognitive advantages, which are discussed in detail.
Phrase structure is built by using a fast algorithm and compact
reference tables. A quantified comparison of different compilation
methods shows that lexical and structural information are most compactly
represented by separate tables. This finding is reconciled to evidence
on the resolution of lexical ambiguity, as an approach to the
modularization of information.
The same design is applied to the efficient computation of long-
distance dependencies. Incremental parsing using bottom-up tabular
algorithms is discussed in detail.
Finally, locality restrictions are calculated by a parametric
algorithm.
Students of linguistics, parsing and psycholinguistics will find this
book a useful resource on issues related to the implementation of
current linguistic theories, using computational and cognitive plausible
algorithms.