Representation and Inference for Natural Language

A First Course in Computational Semantics

Here is the first textbook wholly devoted to computational semantics, a lively subject still in its formative stage. A central question is how to represent meaning in ways usable by computers. Furthermore, can computers distinguish coherent from incoherent utterances, recognize new information in a sentence, or even draw inferences from a natural language passage?

Computer scientists, linguists, logicians, and indeed anyone curious about the role of meaning in human languages, will appreciate where questions such as the above lead this book. After the underlying theoretical issues are thoroughly introduced, complete implementations are presented of various fundamental techniques for computing semantic representations for fragments of natural language and for performing inference with the results. The reader who masters these techniques will be in a good position to appreciate, and critically assess, ongoing developments in computational semantics.

“An exciting combination of standard Montague techniques, modern approaches to underspecification, and the use of first-order theorem provers, all in a book than can be used by advanced undergraduates or graduate students.”
 – Robin Cooper, Gorg University