Fast Statistical Parsing with Parallel Multiple Context-Free Grammars

Krasimir Angelov

Abstract:

We present an algorithm for incremental
statistical parsing with Parallel Multiple
Context-Free Grammars (PMCFG). This
is an extension of the algorithm by Angelov (2009) to which we added statistical ranking. We show that the new algorithm is several times faster than other
statistical PMCFG parsing algorithms on
real-sized grammars. At the same time the
algorithm is more general since it supports
non-binarized and non-linear grammars.
We also show that if we make the
search heuristics non-admissible, the parsing speed improves even further, at the risk
of returning sub-optimal solutions.