The recognition of multiword expressions (MWEs) in a sentence is important for such linguistic analyses as syntactic and semantic parsing, because it is known that combining an MWE into a single token improves accuracy for various NLP tasks, such as dependency parsing and constituency parsing. However, MWEs are not annotated in Penn Treebank. Furthermore, when converting word-based dependency t...

We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of linear constituency. The product model outperforms both components on their respective evaluation metrics, giving the best published figures for unsupervised dependency parsing and unsupervised constituency parsing. We als...

This paper presents a set of experiments performed on parsing the Basque Dependency Treebank. We have applied feature propagation to dependency parsing, experimenting the propagation of several morphosyntactic feature values. In the experiments we have used the output of a parser to enrich the input of a second parser. Both parsers have been generated by Maltparser, a freely data-driven depende...

Much work has been done on building a parser for natural languages, but most of this work has concentrated on supervised parsing. Unsupervised parsing is a less explored area, and unsupervised dependency parser has hardly been tried. In this paper we present two approaches for building an unsupervised dependency parser. One approach is based on learning dependency relations and the other on lea...

Pure statistical parsing systems achieves high in-domain accuracy but performs poorly out-domain. In this paper, we propose two different approaches to produce syntactic dependency structures using a large-scale hand-crafted HPSG grammar. The dependency backbone of an HPSG analysis is used to provide general linguistic insights which, when combined with state-of-the-art statistical dependency p...

Accuracy of dependency parsers is one of the key factors limiting the quality of dependencybased machine translation. This paper deals with the influence of various dependency parsing approaches (and also different training data size) on the overall performance of an English-to-Czech dependency-based statistical translation system implemented in the Treex framework. We also study the relationsh...

This paper is a description of our system developed for SemEval-2016 Task 9: Chinese Semantic Dependency Parsing. We have built a transition-based dependency parser with online reordering, which is not limited to a tree structure and can produce 99.7% of the necessary dependencies while maintaining linear algorithm complexity. To improve parsing quality we used additional techniques such as pre...