In both the linguistic and the language engineering community, the creation and use of annotated text collections (or annotated corpora) is currently a hot topic. Annotated texts are of interest for research as well as for the development of natural language pro cessing (NLP) applications. Unfortunately, the annotation of text material, especially more interesting linguistic annotation, is as yet a difficult task and can entail a substan tial amount of human involvement. Allover the world, work is being done to replace as much as possible of this human effort by computer processing. At the frontier of what can already be done (mostly) automatically we find syntactic wordclass tagging, the annotation of the individual words in a text with an indication of their morpho syntactic classification. This book describes the state of the art in syntactic wordclass tagging. As an attempt to give an overall view of the field, this book is of interest to (at least) two, possibly very different, types of reader. The first type consists of those people who are using, or are planning to use, tagged material and taggers. They will want to know what the possibilities and impossibilities of tagging are, but are not necessarily interested in the internal working of automatic taggers. This, on the other hand, is the main interest of our second type of reader, the builders of automatic taggers and other natural language processing software.

This handbook explores multiple facets of the study of word classes, also known as parts of speech or lexical categories. These categories are of fundamental importance to linguistic theory and description, both formal and functional, and for both language-internal analyses and cross-linguistic comparison. The volume consists of five parts that investigate word classes from different angles. Chapters in the first part address a range of fundamental issues including diversity and unity in word classes around the world, categorization at different levels of structure, the distinction between lexical and functional words, and hybrid categories. Part II examines the treatment of word classes across a wide range of contemporary linguistic theories, such as Cognitive Grammar, Minimalist Syntax, and Lexical Functional Grammar, while the focus of Part III is on individual word classes, from major categories such as verb and noun to minor ones such as adpositions and ideophones. Part IV provides a number of cross-linguistic case studies, exploring word classes in families including Afroasiatic, Sinitic, Mayan, Austronesian, and in sign languages. Chapters in the final part of the book discuss word classes from the perspective of various sub-disciplines of linguistics, ranging from first and second language acquisition to computational and corpus linguistics. Together, the contributions showcase the importance of word classes for the whole discipline of linguistics, while also highlighting the many ongoing debates in the areas and outlining fruitful avenues for future research.

This book addresses the research, analysis, and description of the methods and processes that are used in the annotation and processing of language corpora in advanced, semi-advanced, and non-advanced languages. It provides the background information and empirical data needed to understand the nature and depth of problems related to corpus annotation and text processing and shows readers how the linguistic elements found in texts are analyzed and applied to develop language technology systems and devices. As such, it offers valuable insights for researchers, educators, and students of linguistics and language technology.

This book constitutes the refereed proceedings of the 4th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2009, held in Poznan, Poland, in November 2009. The 52 revised and in many cases substantially extended papers presented in this volume were carefully reviewed and selected from 103 submissions. The contributions are organized in topical sections on speech processing, computational morphology/lexicography, parsing, computational semantics, dialogue modeling and processing, digital language resources, WordNet, document processing, information processing, and machine translation.

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.