Unsupervised dependency parsing aims to learn a dependency grammar from text annotated with only POS tags. Various features and inductive biases are often used to incorporate prior knowledge into learning. One useful type of prior information is that there exist correlations between the parameters of grammar rules involving different POS tags. Previous work employed manually designed features o...

In this paper describes the effects of the evolution of an Italian dependency grammar on a task of multilingual FrameNet acquisition. The task is based on the creation of virtual English/Italian parallel annotation corpora, which are then aligned at dependency level by using two manually encoded grammar based dependency parsers. We show how the evolution of the LAS (Labeled Attachment Score) me...

This paper gives an outline about most important features of GRAALAN (Grammar Abstract Language) used for linguistic knowledge description. GRAALAN is an implementation of theoretical concepts of GDGF (Generative Dependency Grammars with Features) and AVT (Attribute Value Trees). GDGF is based on dependency trees (DT) and a generative process. GDG eliminates some issues of Dependency Grammars D...

Syntactic parsing in NLP is the task of working out the grammatical structure of sentences. Some of the purely formal approaches to parsing such as phrase structure grammar, dependency grammar have been successfully employed for a variety of languages. While phrase structure based constituent analysis is possible for fixed order languages such as English, dependency analysis between the grammat...

We describe a new framework for dependency grammar, with a modular decomposition of immediate dependency and linear precedence. Our approach distinguishes two orthogonal yet mutually constraining structures: a syntactic dependency tree and a topological dependency tree. The syntax tree is nonprojective and even non-ordered, while the topological tree is projective and partially ordered.

Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes...

Induction of synchronous grammars from empirical data has long been a problem unsolved; despite that generative synchronous grammars theoretically suit the machine translation task very well. This fact is mainly due to pervasive structural divergences between languages. This paper presents a statistical approach to learn dependency structure mappings from parallel corpora. The algorithm introdu...

This paper provides an analysis of the representation of various grammatical phenomena in both constituency structure and dependency structure (hereafter c-structure and d-structure), including agreement, case marking, and word order in transitive sentences, as well as three theoretical constructs, and the interface between the form of a sentence and its meaning. There is a crucial structural r...

This paper describes some operational aspects of a language comprehension model which unifies the linguistic theory and the semantic theory in respect to operations. The computational model, called Augmented Dependency Grammar (ADG), formulates not only the linguistic dependency structure of sentences but also the semantic dependency structure using the extended deep case grammar and fleld-orie...

Recently (Rogers, 2004), there have been attempts to step out of the shadow of GES, and to use MTS not only to reformulate and compare existing frameworks, but to utilize the more declarative, clarifying perspective of MTS to also explore extensions of them. This is what we set out to do in this paper as well. We base our work on the model-theoretic meta grammar formalism of Extensible Dependen...