Lexical Ambiguity Resolution

The most frequently used words in English are highly ambiguous; for example, Webster's Ninth New Collegiate Dictionary lists 94 meanings for the word "run" as a verb alone. Yet people rarely notice this ambiguity. Solving this puzzle has commanded the efforts of cognitive scientists for many years. The solution most often identified is "context": we use the context of utterance to determine the proper meanings of words and sentences. The problem then becomes specifying the nature of context and how it interacts with the rest of an understanding system. The difficulty becomes especially apparent in the attempt to write a computer program to understand natural language. Lexical ambiguity resolution (LAR), then, is one of the central problems in natural language and computational semantics research. A collection of the best research on LAR available, this volume offers eighteen original papers by leading scientists. Part I, Computer Models, describes nine attempts to discover the processes necessary for disambiguation by implementing programs to do the job. Part II, Empirical Studies, goes into the laboratory setting to examine the nature of the human disambiguation mechanism and the structure of ambiguity itself. A primary goal of this volume is to propose a cognitive science perspective arising out of the conjunction of work and approaches from neuropsychology, psycholinguistics, and artificial intelligence--thereby encouraging a closer cooperation and collaboration among these fields. Lexical Ambiguity Resolution is a valuable and accessible source book for students and cognitive scientists in AI, psycholinguistics, neuropsychology, or theoretical linguistics.

Sets out state-of-the-art methodological and theoretical advancements to shed light on how bilingual speakers comprehend ambiguous information.

The most frequently used words in English are highly ambiguous; for example, Webster's Ninth New Collegiate Dictionary lists 94 meanings for the word ""run"" as a verb alone. Yet people rarely notice this ambiguity. Solving this puzzle has commanded the efforts of cognitive scientists for many years. The solution most often identified is ""context"": we use the context of utterance to determine the proper meanings of words and sentences. The problem then becomes specifying the nature of context and how it interacts with the rest of an understanding system. The difficulty becomes espe.

The authors present a comprehensive overview of past research in ambiguity in the field of psycholinguistics. Experimental results have often been equivocal in allowing a choice between the single-reading hypothesis and the multiple-reading hypothesis of processing of ambiguous sentences. This text reviews the arguments and experimental results in support of each of these views, and further investigates the contributions of context and thematic constraints in the process of ambiguity resolution. Commentary is also made on the possible hierarchical ordering of difficulty in the treatment of ambiguity, as well as critically related considerations like bias, individual differences, general cognitive strategies for dealing with multiphase representations, and the inherent differences between lexical and syntactic ambiguity.

One of the liveliest forums for sharing psychological, linguistic, philosophical, and computer science perspectives on psycholinguistics has been the annual meeting of the CUNY Sentence Processing Conference. Documenting the state of the art in several important approaches to sentence processing, this volume consists of selected papers that had been presented at the Sixth CUNY Conference. The editors not only present the main themes that ran through the conference but also honor the breadth of the presentations from disciplines including linguistics, experimental psychology, and computer science. The variety of sentence processing topics examined includes: * how evoked brain potentials reflect sentence comprehension * how auditory words are processed * how various sources of grammatical and nongrammatical information are coordinated and used * how sentence processing and language acquisition might be related. This distinctive volume not only presents the most exciting current work in sentence processing, but also places this research into the broader context of theorizing about it.

Semantic interpretation and the resolution of ambiguity presents an important advance in computer understanding of natural language. While parsing techniques have been greatly improved in recent years, the approach to semantics has generally improved in recent years, the approach to semantics has generally been ad hoc and had little theoretical basis. Graeme Hirst offers a new, theoretically motivated foundation for conceptual analysis by computer, and shows how this framework facilitates the resolution of lexical and syntactic ambiguities. His approach is interdisciplinary, drawing on research in computational linguistics, artificial intelligence, montague semantics, and cognitive psychology.

This volume is concerned with how ambiguity and ambiguity resolution are learned, that is, with the acquisition of the different representations of ambiguous linguistic forms and the knowledge necessary for selecting among them in context. Schütze concentrates on how the acquisition of ambiguity is possible in principle and demonstrates that particular types of algorithms and learning architectures (such as unsupervised clustering and neural networks) can succeed at the task. Three types of lexical ambiguity are treated: ambiguity in syntactic categorisation, semantic categorisation, and verbal subcategorisation. The volume presents three different models of ambiguity acquisition: Tag Space, Word Space, and Subcat Learner, and addresses the importance of ambiguity in linguistic representation and its relevance for linguistic innateness.