Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
Statistical properties of probabilistic context-free grammars
Computational Linguistics
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Towards history-based grammars: using richer models for probabilistic parsing
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Head automata and bilingual tiling: translation with minimal representations
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Stochastic lexicalized tree-adjoining grammars
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Computational complexity of probabilistic disambiguation by means of tree-grammars
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Applying Probability Measures to Abstract Languages
IEEE Transactions on Computers
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A novel theoretical framework for describing stochastic grammars is proposed based on a small set of basic random variables that generate tree structures and relate them to surface strings. A number of prominent statistical language models are formulated as stochastic processes over these basic random variables.