Previous studies in data-driven dependency parsing have shown that tree transformations can improve parsing accuracy for specific parsers and data sets. We investigate to what ex...
Inducing a grammar directly from text is one of the oldest and most challenging tasks in Computational Linguistics. Significant progress has been made for inducing dependency gram...
In this paper we describe a new technique for parsing free text: a transformational grammar I is automatically learned that is capable of accurately parsing text into binary-branc...
This paper proposes a new corpus-based approach for deriving syntactic structures and generating parse trees of natural language sentences. The parts of speech (word categories) of...
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...