Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Natural language parsing as statistical pattern recognition
Natural language parsing as statistical pattern recognition
Training and scaling preference functions for disambiguation
Computational Linguistics
A maximum entropy approach to natural language processing
Computational Linguistics
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximum Entropy Modeling with Clausal Constraints
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Parsing inside-out
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
Stochastic attribute-value grammars
Computational Linguistics
Exploiting auxiliary distributions in stochastic unification-based grammars
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
A probabilistic corpus-driven model for lexical-functional analysis
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Two principles of parse preference
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Estimators for stochastic "Unification-Based" grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Issues in Learning Language in Logic
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
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We discuss the probabilistic modeling of constraint-based grammars by log-linear distributions and present a novel technique for statistical inference of the parameters and properties of such models from unannotated training data. We report on an experiment with a log-linear grammar model which employs sophisticated linguistically motivated features of parses as properties of the probability model. We report the results of statistical parameter estimation and empirical evaluation of this model on a small scale. These show that log-linear models on the parses of constraint-based grammars are useful for accurate disambiguation.