Ағылшын Penn Treebank

Recent study shows that parsing accuracy can be largely improved by the joint optimization of part-of-speech (POS) tagging and dependency parsing. However, the POS tagging task does not benefit much …...

This paper presents neural probabilistic parsing models which explore up to third- order graph-based parsing with maximum likelihood training criteria. Two neural network extensions are exploited for per- formance improvement. …...

AbstractWe propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models …...

AbstractWe propose a transition-based bubble parser to perform coordination structure identification and dependency-based syntactic analysis simultaneously. Bubble representations were proposed in the formal linguistics literature decades ago; they enhance dependency …...