This paper presents a new method for the conversion of one style of dependency treebanks into another, using contextual, Constraint Grammar-based transformation rules for both structural changes (attachment) and changes in syntacticfunctional tags (edge labels). In particular, we address the conversion of traditional syntactic dependency annotation into the semantically motivated dependency ann...

Dependency analysis relies on morphosyntactic evidence, as well as semantic evidence. In some cases, however, morphosyntactic evidence seems to be in conflict with semantic evidence. For this reason dependency grammar theories, annotation guidelines and tree-to-dependency conversion schemes often differ in how they analyze various syntactic constructions. Most experiments for which constituent-...

CDG represents a sentence’s grammatical structure as assignments of dependency relations to functional variables associated with each word in the sentence. In this paper, we describe a statistical CDG (SCDG) parser that performs parsing incrementally and evaluate it on the Wall Street Journal Penn Treebank. Using a tight integration of multiple knowledge sources, together with distance modeling...

The Multi-word Expressions (MWE) treatment is a very difficult problem for the Natural Language Processing in general and for Machine Translation in particular. This is true because each word of a MWE can have a specific meaning but the expression can have a totally different meaning both in source and in target language of a translation. The things are complicated also by the fact that the sou...

We show that orthographic cues can be helpful for unsupervised parsing. In the Penn Treebank, transitions between upperand lowercase tokens tend to align with the boundaries of base (English) noun phrases. Such signals can be used as partial bracketing constraints to train a grammar inducer: in our experiments, directed dependency accuracy increased by 2.2% (average over 14 languages having cas...

This paper is an attempt to show that an intermediary level of analysis is an effective way for carrying out various NLP tasks for linguistically similar languages. We describe a process for developing a simple parser for doing such tasks. This parser uses a grammar driven approach to annotate dependency relations (both inter and intra chunk) at an intermediary level. Ease in identifying a part...

We present Pro3Gres, a deep-syntactic, fast dependency parser that combines a handwritten competence grammar with probabilistic performance disambiguation and that has been used in the biomedical domain. We discuss its performance in the domain adaptation open submission. We achieve average results, which is partly due to difficulties in mapping to the dependency representation used for the sha...

This paper investigates transforms of split dependency grammars into unlexicalised context-free grammars annotated with hidden symbols. Our best unlexicalised grammar achieves an accuracy of 88% on the Penn Treebank data set, that represents a 50% reduction in error over previously published results on unlexicalised dependency parsing.

The theory of conceptual structures serves as a common basis for natural language processing and medical concept representation. We present a PROLOG-based formalization of dependency grammar that can accommodate conceptual structures in its dependency rules. First results indicate that this formalization provides an operational basis for the implementation of medical language parsers and for th...

A framework for concurrent, object-oriented natural language parsing is introduced. The underlying grammar model is fully lexicalized, headdriven, dependency-oriented, and structured along multiple inheritance hierarchies. The computation model relies upon the actor paradigm, with concurrency entering through asynchronous message passing. Protocols for establishing basic dependency relations an...