This book presents the author's research on automatic learning procedures for categorial grammars of natural languages. The research program spans a number of intertwined disciplines, including syntax, semantics, learnability theory, logic, and computer science. The theoretical framework employed is an extension of categorial grammar that has come to be called multimodal or type-logical grammar. The first part of the book presents an expository summary of how grammatical sentences of any language can be deduced with a specially designed logical calculus that treats syntactic categories as its formulae. Some such Universal Type Logic is posited to underlie the human language faculty, and all linguistic variation is captured by the different systems of semantic and syntactic categories which are assigned in the lexicons of different languages. The remainder of the book is devoted to the explicit formal development of computer algorithms which can learn the lexicons of type logical grammars from learning samples of annotated sentences. The annotations consist of semantic terms expressed in the lambda calculus, and may also include an unlabeled tree-structuring over the sentence. The major features of the research include the following: We show how the assumption of a universal linguistic component---the logic of language---is not incompatible with the conviction that every language needs a different system of syntactic and semantic categories for its proper description. The supposedly universal linguistic categories descending from antiquity (noun, verb, etc.) are summarily discarded. Languages are here modeled as consisting primarily of sentence trees labeled with semantic structures; a new mathematical class of such term-labeled tree languages is developed which cross-cuts the well-known Chomsky hierarchy and provides a formal restrictive condition on the nature of human languages. The human language acquisition mechanism is postulated to be biased, such that it assumes all input language samples are drawn from the above "syntactically homogeneous" class; in this way, the universal features of human languages arise not just from the innate logic of language, but also from the innate biases which govern language learning. This project represents the first complete explicit attempt to model the aquisition of human language since Steve Pinker's groundbreaking 1984 publication, "Language Learnability and Language Development."

"English is so illogical!" It is generally believed that English is a language of exceptions. For many, learning to spell and read is frustrating. For some, it is impossible... especially for the 29% of Americans who are functionally illiterate. But what if the problem is not the language itself, but the rules we were taught? What if we could see the complexity of English as a powerful tool rather than a hindrance? --Denise Eide Uncovering the Logic of English challenges the notion that English is illogical by systematically explaining English spelling and answering questions like "Why is there a silent final E in have, large, and house?" and "Why is discussion spelled with -sion rather than -tion?" With easy-to-read examples and anecdotes, this book describes: - the phonograms and spelling rules which explain 98% of English words - how English words are formed and how this knowledge can revolutionize vocabulary development - how understanding the reasons behind English spelling prevents students from needing to guess The author's inspiring commentary makes a compelling case that understanding the logic of English could transform literacy education and help solve America's literacy crisis. Thorough and filled with the latest linguistic and reading research, Uncovering the Logic of English demonstrates why this systematic approach should be as foundational to our education as 1+1=2.

This volume has its origins in the ?rst Learning Language in Logic (LLL) wo- shop which took place on 30 June 1999 in Bled, Slovenia immediately after the Ninth International Workshop on Inductive Logic Programming (ILP’99) and the Sixteenth International Conference on Machine Learning (ICML’99). LLL is a research area lying at the intersection of computational linguistics, machine learning, and computational logic. As such it is of interest to all those working in these three ?elds. I am pleased to say that the workshop attracted subm- sions from both the natural language processing (NLP) community and the ILP community, re?ecting the essentially multi-disciplinary nature of LLL. Eric Brill and Ray Mooney were invited speakers at the workshop and their contributions to this volume re?ect the topics of their stimulating invited talks. After the workshop authors were given the opportunity to improve their papers, the results of which are contained here. However, this volume also includes a substantial amount of two sorts of additional material. Firstly, since our central aim is to introduce LLL work to the widest possible audience, two introductory chapters have been written. Dzeroski, ? Cussens and Manandhar provide an - troduction to ILP and LLL and Thompson provides an introduction to NLP.

How is the meaning of natural language interpreted? Taking as its point of departure the logical problem of natural language acquisition, this book elaborates a theory of meaning based on syntactical rather than semantical processes. Copyright © Libri GmbH. All rights reserved.

The authors offer a clear, succinct and basic introduction to set theory and formal logic for linguists.

The Logic of Our Language teaches the practical and everyday application of formal logic. Rather than overwhelming the reader with abstract theory, Jackson and McLeod show how the skills developed through the practice of logic can help us to better understand our own language and reasoning processes. The authors’ goal is to draw attention to the patterns and logical structures inherent in our spoken and written language by teaching the reader how to translate English sentences into formal symbols. Other logical tools, including truth tables, truth trees, and natural deduction, are then introduced as techniques for examining the properties of symbolized sentences and assessing the validity of arguments. A substantial number of practice questions are offered both within the book itself and as interactive activities on a companion website.