Robust stochastic parsing using the inside-outside algorithm
cmp-lg
2008-02-03 v1 Computation and Language
Abstract
The paper describes a parser of sequences of (English) part-of-speech labels which utilises a probabilistic grammar trained using the inside-outside algorithm. The initial (meta)grammar is defined by a linguist and further rules compatible with metagrammatical constraints are automatically generated. During training, rules with very low probability are rejected yielding a wide-coverage parser capable of ranking alternative analyses. A series of corpus-based experiments describe the parser's performance.
Cite
@article{arxiv.cmp-lg/9412006,
title = {Robust stochastic parsing using the inside-outside algorithm},
author = {Briscoe and Ted and Waegner and Nick},
journal= {arXiv preprint arXiv:cmp-lg/9412006},
year = {2008}
}
Comments
Revised and updated version of paper from AAAI Workshop on Probabilistically-based Natural Language Processing Techniques, 1992, 16 pages, uuencoded, compressed postscript