Probabilistic Parsing Using Left Corner Language Models (1997)
| Venue: | In Proceedings of the 5th ACL/SIGPARSE International Workshop on Parsing Technologies. MIT |
| Citations: | 31 - 2 self |
BibTeX
@INPROCEEDINGS{Manning97probabilisticparsing,
author = {Christopher D. Manning and Bob Carpenter},
title = {Probabilistic Parsing Using Left Corner Language Models},
booktitle = {In Proceedings of the 5th ACL/SIGPARSE International Workshop on Parsing Technologies. MIT},
year = {1997},
pages = {147--158},
publisher = {Kluwer Academic Publishers}
}
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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. 1 Introduction For context-free grammars (CFGs), there is a well-known standard probabilistic version, Probabilistic ContextFree Grammars (PCFGs), which have been thoroughly investigated [Suppes, 1970, Sankoff, 1971, Baker, 1979, Lari and Young, 1990, Kupiec, 1991, Jelinek et al., 1992, Charniak...
