Representation and Inference for Natural Language: A First Course in Computational Semantics

Francis Jeffry Pelletier
2006 Computational Linguistics  
Computational semantics is the study of how to represent meaning in a way that computers can use. For the authors of this textbook, this study includes the representation of the meaning of natural language in logic formalisms, the recognition of certain relations that hold within this formalization (such as synonymy, consistency, and implication), and the computational implementation of all this. I think that, while there probably are not many courses devoted to computational semantics, this
more » ... k could profitably be incorporated into more traditional computational linguistics courses, especially when two courses are offered serially. The material here could be spread out and integrated into parts of a more standard pair of these courses, and it would result in a substantial widening of the knowledge that students come away with from these courses. The introduction of this book traces the history of computational semantics, with a goal of justifying the enterprise in the face of the modern emphasis on statistical natural language processing. Besides this introduction, the book contains six substantial chapters and four short appendices. There is also a very extensive suite of material online at a Web site maintained by the authors. Chapter 1 is an introduction to first-order logic, but with a twist that underscores the particular outlook taken in this book. There is a very short introduction to the notion of a model of a set of quantifier-free sentences, followed by an equally short discussion of the interpretation of quantifiers in a model. With respect to quantifier-free sentences, students are referred to the three-page Appendix B on propositional logic, where truth-tables are covered. The innovations start with the introduction of three "inference tasks": querying, consistency checking, and informativity checking. These correspond to the logical concepts of satisfiability (of a given formula in a given model), consistency (whether there is a model that satisfies a given formula), and validity (whether a formula is true in all models, or, equivalently, whether a given argument is valid). Although the notions of querying, etc., are thus merely renamings of standard logical notions, it seems to me that the renaming is particularly apposite in the setting of a textbook for non-logicians, especially since much is to be done computationally with these notions in the enterprise of computational semantics. Much of the remainder of chapter 1 consists of a gentle introduction to Prolog and using it to check formulas for well-formedness and to build model checkers with the goal of implementing the querying task.
doi:10.1162/coli.2006.32.2.283 fatcat:x5lzseuu4zdi7nfgjthpb6ya2a