Natural language parsing with data-driven dependency-based frameworks has received an
increasing amount of attention in recent years, as observed in the shared tasks hosted by …

We describe a two-stage optimization of the MaltParser system for the ten languages in the
multilingual track of the CoNLL 2007 shared task on dependency parsing. The first stage …

To facilitate future research in unsupervised induction of syntactic structure and to
standardize best-practices, we propose a tagset that consists of twelve universal part-of …

We introduce new methods for estimating and evaluating embeddings of words in more than
fifty languages in a single shared embedding space. Our estimation methods, multiCluster …

Parsing unrestricted text is useful for many language technology applications but requires
parsing methods that are both robust and efficient. MaltParser is a language-independent …

Abstract The Conference on Computational Natural Language Learning features a shared
task, in which participants train and test their learning systems on the same data sets. In …

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 …

We describe a method for prediction of linguistic structure in a language for which only
unlabeled data is available, using annotated data from a set of one or more helper …

The paper addresses the challenge of converting MIDT, an existing dependency–based
Italian treebank resulting from the harmonization and merging of smaller resources, into the …

To investigate the feasibility of using complex networks in the study of linguistic typology, this
paper builds and explores 15 linguistic complex networks based on the dependency …