Corpus-based grammar induction relies on using many hand-parsed sentences as training examples. However, the construction of a training corpus with detailed syntactic analysis for every sentence is a ...
We present an empirical study of the applicability of Probabilistic Lexicalized Tree Insertion Grammars (PLTIG), a lexicalized counterpart to Probabilistic Context-Free Grammars (PCFG), to problems in...
We present an empirical study of the applicability of Probabilistic Lexicalized Tree Insertion Grammars (PLTIG), a lexicalized counterpart to Probabilistic Context-Free Grammars (PCFG), to problems in...
Corpus-based grammar induction relies on using many hand-parsed sentences as training examples. However, the construction of a training corpus with detailed syntactic analysis for every sentence is a ...
this paper were produced using some features that were manually coded, once developed, they could be used in reverse to enhance the comprehensibility of text generation systems or the naturalness of t...
this paper were produced using some features that were manually coded, once developed, they could be used in reverse to enhance the comprehensibility of text generation systems or the naturalness of t...
this paper, we describe a framework for developing probabilistic classifiers in natural language processing. Our focus is on formulating models that capture the most important interdependencies among ...