We demonstrate that replacing an LSTM encoder with a self-attentive architecture can lead
to improvements to a state-of-the-art discriminative constituency parser. The use of attention …

We show that constituency parsing benefits from unsupervised pre-training across a variety
of languages and a range of pre-training conditions. We first compare the benefits of no pre …

We present extensions to a continuous-state dependency parsing method that makes it
applicable to morphologically rich languages. Starting with a high-performance transition …

This paper reports on the first shared task on statistical parsing of morphologically rich lan-
guages (MRLs). The task features data sets from nine languages, each available both in …

This paper describes a parsing model that combines the exact dynamic programming of
CRF parsing with the rich nonlinear featurization of neural net approaches. Our model is …

This first joint meeting on Statistical Parsing of Morphologically Rich Languages and
Syntactic Analysis of Non-Canonical English (SPMRL-SANCL) featured a shared task on …

In this paper we focus on the problem of question ranking in community question answering
(cQA) forums in Arabic. We address the task with machine learning algorithms using …

In this paper, we introduce a new approach for joint segmentation, POS tagging and
dependency parsing. While joint modeling of these tasks addresses the issue of error …

We present a parser that relies primarily on extracting information directly from surface
spans rather than on propagating information through enriched grammar structure. For …

In this paper, we investigate various strategies to predict both syntactic dependency parsing
and contiguous multiword expression (MWE) recognition, testing them on the dependency …