Up to now there has been no scientific publication on natural lan guage research that presents a broad and complex description of the current problems of parsing in the context of Artificial Intelli gence. However, there are many interesting results from this domain appearing mainly in numerous articles published in pro fessional journals. In view of this situation, the objective of this book is to enable scientists from different countries to present the results of their research on natural language parsing in the form of more detailed papers than would be possible in professional jour nals. This book thus provides a collection of studies written by well known scientists whose earlier publications have greatly contributed to the development of research on natural language parsing. Jaime G. Carbonell and Philip J. Hayes present in their paper "Robust Parsing Using Multiple Construction-Specific Strategies" two small experimental parsers, implemented to illustrate the advantages of a multi-strategy approach to parsers, with strategies selected according to the type of construction being parsed at any given time. This presentation is followed by the description of a parsing algorithm, integrating some of the best features of the two smaller parsers, including case-frame instantiation and partial pat tern-matching strategies.

presupposition fails, we now give a short introduction into Unification Grammar. Since all implementations discussed in this volume use PROLOG (with the exception of BlockjHaugeneder), we felt that it would also be useful to explain the difference between unification in PROLOG and in UG. After the introduction to UG we briefly summarize the main arguments for using linguistic theories in natural language processing. We conclude with a short summary of the contributions to this volume. UNIFICATION GRAMMAR 3 Feature Structures or Complex Categories. Unification Grammar was developed by Martin Kay (Kay 1979). Martin Kay wanted to give a precise defmition (and implementation) of the notion of 'feature'. Linguists use features at nearly all levels of linguistic description. In phonetics, for instance, the phoneme b is usually described with the features 'bilabial', 'voiced' and 'nasal'. In the case of b the first two features get the value +, the third (nasal) gets the value -. Feature value pairs in phonology are normally represented as a matrix. bilabial: + voiced: + I nasal: - [Feature matrix for b.] In syntax features are used, for example, to distinguish different noun classes. The Latin noun 'murus' would be characterized by the following feature-value pairs: gender: masculin, number: singular, case: nominative, pred: murus. Besides a matrix representation one frequently fmds a graph representation for feature value pairs. The edges of the graph are labelled by features. The leaves denote the value of a feature.

The book presents a wide range of recent research results about parsing schemata, introducing formal frameworks and theoretical results while keeping a constant focus on applicability to practical parsing problems. The first part includes a general introduction to the parsing schemata formalism that contains the basic notions needed to understand the rest of the parts. Thus, this compendium can be used as an introduction to natural language parsing, allowing postgraduate students not only to get a solid grasp of the fundamental concepts underlying parsing algorithms, but also an understanding of the latest developments and challenges in the field. Researchers in computational linguistics will find novel results where parsing schemata are applied to current problems that are being actively researched in the computational linguistics community (like dependency parsing, robust parsing, or the treatment of non-projective linguistics phenomena). This book not only explains these results in a more detailed, comprehensive and self-contained way, and highlights the relations between them, but also includes new contributions that have not been presented.

Given that context-free grammars (CFG) cannot adequately describe natural languages, grammar formalisms beyond CFG that are still computationally tractable are of central interest for computational linguists. This book provides an extensive overview of the formal language landscape between CFG and PTIME, moving from Tree Adjoining Grammars to Multiple Context-Free Grammars and then to Range Concatenation Grammars while explaining available parsing techniques for these formalisms. Although familiarity with the basic notions of parsing and formal languages is helpful when reading this book, it is not a strict requirement. The presentation is supported with many illustrations and examples relating to the different formalisms and algorithms, and chapter summaries, problems and solutions. The book will be useful for students and researchers in computational linguistics and in formal language theory.

CICLing 2004 was the 5th Annual Conference on Intelligent Text Processing and Computational Linguistics; see www.CICLing.org. CICLing conferences are intended to provide a balanced view of the cutting-edge developments in both theoretical foundations of computational linguistics and the practice of natural language text processing with its numerous applications. A feature of CICLing conferences is their wide scope that covers nearly all areas of computational linguistics and all aspects of natural language processing applications. These conferences are a forum for dialogue between the specialists working in the two areas. This year we were honored by the presence of our invited speakers Martin KayofStanfordUniversity,PhilipResnikoftheUniversityofMaryland,Ricardo Baeza-Yates of the University of Chile, and Nick Campbell of the ATR Spoken Language Translation Research Laboratories. They delivered excellent extended lectures and organized vivid discussions. Of129submissionsreceived(74fullpapersand44shortpapers),aftercareful international reviewing 74 papers were selected for presentation (40 full papers and35shortpapers),writtenby176authorsfrom21countries:Korea(37),Spain (34), Japan (22), Mexico (15), China (11), Germany (10), Ireland (10), UK (10), Singapore (6), Canada (3), Czech Rep. (3), France (3), Brazil (2), Sweden (2), Taiwan (2), Turkey (2), USA (2), Chile (1), Romania (1), Thailand (1), and The Netherlands (1); the ?gures in parentheses stand for the number of authors from the corresponding country.

This book describes the framework of inductive dependency parsing, a methodology for robust and efficient syntactic analysis of unrestricted natural language text. Coverage includes a theoretical analysis of central models and algorithms, and an empirical evaluation of memory-based dependency parsing using data from Swedish and English. A one-stop reference to dependency-based parsing of natural language, it will interest researchers and system developers in language technology, and is suitable for graduate or advanced undergraduate courses.