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...
Supertagging is an important technique for deep syntactic analysis. A supertagger is usually trained independently of the parser using a sequence labeling method. This presents an...
ScalaBison is a parser generator accepting bison syntax and generating a parser in Scala. The generated parser uses the idea of "recursive ascent-descent parsing," that ...
The paper describes an approach to extend the coverage of a Link Grammar based parser on the constructions that are not being handled currently by the grammar. There are about thir...
We investigate the effectiveness of selftraining PCFG grammars with latent annotations (PCFG-LA) for parsing languages with different amounts of labeled training data. Compared to...
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
This paper presents experiments which combine a grammar-driven and a datadriven parser. We show how the conversion of LFG output to dependency representation allows for a techniqu...
We compare the CCG parser of Clark and Curran (2007) with a state-of-the-art Penn Treebank (PTB) parser. An accuracy comparison is performed by converting the CCG derivations into...
Abstract In this paper we assess to what extent the available Portuguese treebanks and available probabilistic parsers are suitable for outof-the-box robust parsing of Portuguese. ...