DCG induction using MDL and parsed corpora
Learning language in logic
Applying Probability Measures to Abstract Languages
IEEE Transactions on Computers
A Stochastic Syntax Analysis Procedure and Its Application to Pattern Classification
IEEE Transactions on Computers
A priority model for named entities
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Language Correction Using Probabilistic Grammars
IEEE Transactions on Computers
A priority model for named entities
LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
Constructing parse forests that include exactly the n-best PCFG trees
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
On stochastic context-free languages
Information Sciences: an International Journal
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The problem of assigning a probability to each string of a language L(G) generated by a grammar G is considered. Two methods are considered. One method assigns a probability to each production associated with G and the other assigns the probabilities on the basis of particular features of the language. Several necessary conditions that must be satisfied by these probability assignment techniques if they are to be consistant are presented. The problem of recognizing languages is also considered. It is shown that under some conditions it is possible to recognize a non finitestate language with a finite state acceptor if one is willing to accept a small probability of making an error.