We use a statistical method to select the most probable structure or parse for a given sentence. It takes as input the dependency structures generated for the sentence by a depend...
Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at r...
Tomita devised a method of generalized LR GLR parsing to parse ambiguous grammars e ciently. A GLR parser uses linear-time LR parsing techniques as long as possible, falling back...
Abstract. A top-down parsing algorithm has been constructed to accommodate any form of ambiguous context-free grammar, augmented with semantic rules with arbitrary attribute depend...
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinatio...