Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Supertagging: an approach to almost parsing
Computational Linguistics
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Structural disambiguation with constraint propagation
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Combining unsupervised and supervised methods for PP attachment disambiguation
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
What to do when lexicalization fails: parsing German with suffix analysis and smoothing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Guiding a constraint dependency parser with supertags
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The importance of supertagging for wide-coverage CCG parsing
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The benefit of stochastic PP attachment to a rule-based parser
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A statistical constraint dependency grammar (CDG) parser
IncrementParsing '04 Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together
Parsing unrestricted german text with defeasible constraints
CSLP'04 Proceedings of the First international conference on Constraint Solving and Language Processing
Guiding a constraint dependency parser with supertags
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The benefit of stochastic PP attachment to a rule-based parser
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Sentence fusion via dependency graph compression
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A log-linear model with an n-gram reference distribution for accurate HPSG parsing
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Co-parsing with competitive models
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Scalable discriminative parsing for German
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Dependency tree based sentence compression
INLG '08 Proceedings of the Fifth International Natural Language Generation Conference
Morphological and syntactic case in statistical dependency parsing
Computational Linguistics
| Hi-index | 0.00 |
In this paper we investigate the benefit of stochastic predictor components for the parsing quality which can be obtained with a rule-based dependency grammar. By including a chunker, a supertagger, a PP attacher, and a fast probabilistic parser we were able to improve upon the baseline by 3.2%, bringing the overall labelled accuracy to 91.1% on the German NEGRA corpus. We attribute the successful integration to the ability of the underlying grammar model to combine uncertain evidence in a soft manner, thus avoiding the problem of error propagation.