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 …

Dependency grammar is a descriptive and theoretical tradition in linguistics that can be
traced back to antiquity. It has long been influential in the European linguistics tradition and …

Every year, the Conference on Computational Natural Language Learning (CoNLL) features
a shared task, in which participants train and test their learning systems on the same data …

In all previous work on deep multi-task learning we are aware of, all task supervisions are on
the same (outermost) layer. We present a multi-task learning architecture with deep bi …

Multiword expressions (MWEs) are a class of linguistic forms spanning conventional word
boundaries that are both idiosyncratic and pervasive across different languages. The …

We present a new collection of treebanks with homogeneous syntactic dependency
annotation for six languages: German, English, Swedish, Spanish, French and Korean. To …

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 …

Distributed word representations (word embeddings) have recently contributed to
competitive performance in language modeling and several NLP tasks. In this work, we train …

We introduce a novel architecture for dependency parsing:\emph {stack-pointer
networks}(\textbf {\textsc {StackPtr}}). Combining pointer networks~\citep …

We assume that the tokenization of a sentence is fixed and known at parsing time. That is to
say that dependency parsers will always operate on a pre-tokenized input and are not …