In Data Oriented Parsing (DOP), an annotated corpus is used as a stochastic grammar. An input string is parsed by combining subtrees from the corpus. As a consequence, one parse t...
We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...
This paper reports the first part of a project that aims to develop a knowledge extraction and knowledge discovery system that extracts causal knowledge from textual databases. In...
Two apparently opposing DOP models exist in the literature: one which computes the parse tree involving the most frequent subtrees from a treebank and one which computes the parse...
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than it...
This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree....
We describe the mechanisation of SLR parsing, covering background properties of context-free languages and grammars, as well as the construction of an SLR automaton. Among the vari...
This paper describes an Ei el system for rapid testing of grammars. Grammars are de ned in an extended BNF notation that allows actions on the parse tree nodes to be de ned as add...
Identifying repeating structural regularities in circuits allows the minimization of synthesis, optimization, and layout e orts. We introduce in this paper a novel method for ident...