Probabilistic Parsing Using Left Corner Language Models

1997/11/17 by Christopher D. Manning, Bob Carpenter
Computer Science · #cmp-lg #cs.CL

paper · pdf

published as Proceedings of the Fifth International Workshop on Parsing Technologies, MIT, Boston MA, 1997 · 12 pages, uses iwpt97.sty

arxiv created 1997/11/17 · arxiv updated 2009/11/30

Abstract

We introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We show that the left-corner approach provides an advantage over simple top-down probabilistic context-free grammars in parsing the Wall Street Journal using a grammar induced from the Penn Treebank. We also conclude that the Penn Treebank provides a fairly weak testbed due to the flatness of its bracketings and to the obvious overgeneration and undergeneration of its induced grammar.

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