The inherent robustness of a system might be an important prerequisite for an incremental parsing model to the effect that grammaticality requirements on full sentences may be suspended or allowed to be violated transiently. However, we present additional means that allow the grammarian to model prefix-analyses by altering a grammar for non-incremental parsing in a controlled way. This is done ...

An open problem in dependency parsing is the accurate and efficient treatment of non-projective structures. We propose to attack this problem using chart-parsing algorithms developed for mildly contextsensitive grammar formalisms. In this paper, we provide two key tools for this approach. First, we show how to reduce nonprojective dependency parsing to parsing with Linear Context-Free Rewriting...

 Most data-driven dependency parsing approaches assume that sentence structure is represented as trees. Although trees have several desirable properties from both computational and linguistic perspectives, the structure of linguistic phenomena that goes beyond shallow syntax often cannot be fully captured by tree representations. We present a parsing approach that is nearly as simple as curren...

We investigate statistical dependency parsing of two closely related languages, Croatian and Serbian. As these two morphologically complex languages of relaxed word order are generally under-resourced – with the topic of dependency parsing still largely unaddressed, especially for Serbian – we make use of the two available dependency treebanks of Croatian to produce state-of-the-art parsing mod...

We propose a dependency parsing pipeline, in which the parsing of long-distance projections and localized dependencies are explicitly decomposed at the input level. A chosen baseline dependency parsing model performs only on ’carved’ sequences at the second stage, which are transformed from coarse constituent parsing outputs at the first stage. When k-best constituent parsing outputs are kept, ...

Using the SemEval-2014 Task 8 data, we profile the syntactic tree parsing techniques for semantic graph parsing. In particular, we implement different transitionbased and graph-based models, as well as a parser ensembler, and evaluate their effectiveness for semantic dependency parsing. Evaluation gauges how successful data-driven dependency graph parsing can be by applying existing techniques.

The aim of Evalita Parsing Task is at defining and extending Italian state of the art parsing by encouraging the application of existing models and approaches. As in the Evalita’07 and ’09, the Task is organized around two tracks, i.e. Dependency Parsing and Constituency Parsing. In this paper, we describe only the Dependency Parsing track by presenting the data sets for development and testing...

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 system for data-driven dependency parsing that can be used to induce a parser for a new language from a treebank sample in a simple yet flexible manner. Experimental evaluation confirms that MaltParser can achieve rob...

Part-of-speech (POS) is an indispensable feature in dependency parsing. Current research usually models POS tagging and dependency parsing independently. This may suffer from error propagation problem. Our experiments show that parsing accuracy drops by about 6% when using automatic POS tags instead of gold ones. To solve this issue, this paper proposes a solution by jointly optimizing POS tagg...

In recent years, research in parsing has extended in several new directions. One of these directions is concerned with parsing languages other than English. Treebanks have become available for many European languages, but also for Arabic, Chinese, or Japanese. However, it was shown that parsing results on these treebanks depend on the types of treebank annotations used [ , ]. Another direction ...