We present a comparative error analysis of the two dominant approaches in datadriven dependency parsing: global, exhaustive, graph-based models, and local, greedy, transition-base...
Language and image understanding are two major goals of artificial intelligence which can both be conceptually formulated in terms of parsing the input signal into a hierarchical ...
Leo Zhu, Yuanhao Chen, Yuan Lin, Chenxi Lin, Alan ...
In this paper we investigate the benefit of stochastic predictor components for the parsing quality which can be obtained with a rule-based dependency grammar. By including a chun...
We analyze estimation methods for DataOriented Parsing, as well as the theoretical criteria used to evaluate them. We show that all current estimation methods are inconsistent in ...
How can proteins fold so quickly into their unique native structures? We show here that there is a natural analogy between parsing and the protein folding problem, and demonstrate...