The ability of systems to process natural language is one of the most tangible results of the evolution of artificial intelligence (AI) in the last decade. Conversational interfaces--speech or text--are everywhere: in our Global Positioning System (GPS) apps, behind customer service systems, and even in healthcare. These applications, and many others to come in the near future, are possible due to advances in computational semantics, an area which lies at the intersection of logic, linguistics, information theory, and software engineering.

Linguistic fundamentals for natural language processing II is a thorough introduction to the field, meant for students and information technology (IT) professionals wanting to understand the nuances of human language and how it can be processed by systems. Through 100 small, self-contained articles--which the authors call “vignettes”--the conceptual wealth of computational semantics is scoped and made accessible to beginners.

This is no small feat. Just like language is the cornerstone of human intelligence, computational semantics has a key role in the development of AI. The complexity of the field mirrors the complexity of human language.

The concepts of context, ambiguity, entity reference and coreference, modal subordination, implied meaning in dialogues, anaphora, and so on are discussed and grounded in practical examples. The main computational strategies for dealing with meaning, namely lexical and compositional semantics, are also covered.

Even though the book centers on the pragmatic aspects of how computers process meaning, there is plenty of current academic references that researchers can leverage. Brief and accessible in this case doesn’t mean scientifically unsound; quite the contrary.

As good as what this book provides is, it is also important to point out that it is not designed to help in building natural language processing (NLP) systems. Readers will have to look elsewhere for algorithms for lexical, syntactic, or semantic analysis, or for a discussion of NLP tasks. Still, this book will equip them with the vocabulary and awareness needed to tackle NLP systems and research literature.