Abstract. The development of a syntactic textual entailment system that compares the dependency relations in both the text and the hypothesis has been reported. The Stanford Depend...
Partha Pakray, Alexander F. Gelbukh, Sivaji Bandyo...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Large-scale parsing is still a complex and timeconsuming process, often so much that it is infeasible in real-world applications. The parsing system described here addresses this ...
We present experiments with a dependency parsing model defined on rich factors. Our model represents dependency trees with factors that include three types of relations between t...
Previous studies of data-driven dependency parsing have shown that the distribution of parsing errors are correlated with theoretical properties of the models used for learning an...