Code

Other/Unknown

C++

Dependency parsing is a lightweight syntactic formalism that relies on lexical relationships between words. Nonprojective dependency grammars may generate languages that are not context-free, offering a formalism that is arguably more adequate for some natural languages. Statistical parsers, learned from treebanks, have achieved the best performance in this task. While only local models (arc-factored) allow for exact inference, it has been shown that including non-local features and performing approximate inference can greatly increase performance. This package contains a C++ implementation of a dependency parser. This package allows: learning a parser/tagger from a treebank, running a parser/tagger on new data, evaluating the results against a gold-standard.