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Ontological semantics

TLDR
This book is divided into two parts: a philosophical part I and a practical part II, in which the authors present their text-meaning representation (TMR) and demonstrate how it is used in language analysis and critique many alternative views of semantics.
Abstract
In this book, Nirenburg and Raskin present an important body of work in computational linguistics that they and their colleagues have been developing over the past 20 years. For a unifying perspective, they organize their assumptions, theories, and techniques around the theme of ontological semantics. Along the way, they critique many alternative views of semantics, which they distinguish from their own. Their analyses contribute to a much-needed debate about the history and future of computational linguistics, but to preserve some balance, teachers and students should keep a few of the alternatives on their reference shelf. The book is divided into two parts: a philosophical part I and a practical part II. The first part consists of an introductory chapter 1 and four chapters that survey important but controversial issues about linguistics, both theoretical and computational. In those chapters, the authors make a good case for their version of ontological semantics, but the alternatives are not treated in detail. In part II, the authors present their text-meaning representation (TMR) and demonstrate how it is used in language analysis. Any discussion of technical material must use some notation, and TMR is sufficiently flexible to illustrate a wide range of semantic-based methods that could be adapted to many other formalisms. For most readers, part II would be the more important. Chapter 1 is a good 25-page overview of computational linguistics with an emphasis on semantics. Students and novices, however, need examples, and none are given until chapter 6. The authors suggest that ‘‘a well-prepared and/or uninterested reader’’ skip the remainder of part I and go straight to chapter 6, which begins with an excellent five-page example. The authors follow that advice when they teach courses from this text. In Chapter 2, the authors present their ‘‘Prolegomena to the Philosophy of Linguistics.’’ Their ideas are well taken, and some are as old as Socrates: Examine the assumptions, challenge conventional wisdom, and test conclusions against experience. The basis of their approach is what they call the four components of a scientific theory:

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Citations
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Situations and Attitudes.

TL;DR: Barwise and Perry as discussed by the authors tackle the slippery subject of ''meaning, '' a subject that has long vexed linguists, language philosophers, and logicians, and they tackle it in this book.
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Philosophy and the Mirror of Nature

TL;DR: Rorty's philosophy and the mirror of nature brings to light the deep sense of crisis within the profession of academic philosophy which is similar to the paralyzing pluralism in contemporary theology and the inveterate indeterminacy of literary criticism as mentioned in this paper.
References
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Machine learning

TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
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WordNet : an electronic lexical database

Christiane Fellbaum
- 01 Sep 2000 - 
TL;DR: The lexical database: nouns in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.