Context-free grammars cannot be identified in the limit from positive examples (Gold, 1967), yet natural language grammars are more powerful than context-free grammars and humans ...
Tim Oates, Tom Armstrong, Justin Harris, Mark Nejm...
In traditional multi-instance (MI) learning, a single positive instance in a bag produces a positive class label. Hence, the learner knows how the bag’s class label depends on th...
Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
Determining the semantic role of sentence constituents is a key task in determining sentence meanings lying behind a veneer of variant syntactic expression. We present a model of n...
Cynthia A. Thompson, Roger Levy, Christopher D. Ma...
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...