This is a textbook introduction to the Lexical-Functional Grammar (LFG) syntactic framework. that would be accessible to any linguist with a general f...moreThis is a textbook introduction to the Lexical-Functional Grammar (LFG) syntactic framework. that would be accessible to any linguist with a general familiarity with syntactic theory. It introduces the formalism and shows how it can be applied to standard syntacitic phenomena such as binding and control. There is a relatively short set of problems at the back of the book--enough for a reader to check their own understanding, though probably not enough to base a class around. The exposition is clear. This is the best book I've seen for teaching yourself LFG.

Mary Dalrymple's Lexical-Functional Grammar is another good LFG book that covers much of the same terrain. Unlike Bresnan's book, it is not a textbook, so there are no problem sets, and there is a greater emphasis on describing the syntactic phenomena that motivated the creation of LFG.

An interesting companion would be Syntactic Theory: A Formal Introduction, a textbook about Head-Driven Phase Structure Grammar (HPSG). Though HPSG and LFG employ different formal mechanisms, they share many of the same design philosophies, so a comparison is illuminating. (less)

Part nuts-and-bolts computational linguistics articles and part cri de coeur from a researcher who is exasperated at the hand-wavy route much theoreti...morePart nuts-and-bolts computational linguistics articles and part cri de coeur from a researcher who is exasperated at the hand-wavy route much theoretical linguistics has taken. I am sympathetic to the latter, but bought the book for the former, specifically the chapter "Good-Turing frequency estimation without tears", a detailed tutorial on this smoothing technique that I couldn't find anywhere else. (less)

I purchased this more at less at random when I was first investigating the field of natural language processing and haven't looked at it much since. T...moreI purchased this more at less at random when I was first investigating the field of natural language processing and haven't looked at it much since. The focus is on deterministic methods, e.g. parsing, unification, and semantic data structures. There is nothing about probabilistic methods. May be a decent reference for the non-stochastic side of things; I really haven't read enough to know.(less)

Highlights of this book are a good intuitive description of smoothing and an excellent exposition on the Early parser...This book and Foundations of...moreHighlights of this book are a good intuitive description of smoothing and an excellent exposition on the Early parser...This book and Foundations of Statistical Natural Language Processing by Christopher D. Manning and Hinrich Schütze are the standard textbooks in natural language processing. For my money, Manning and Schütze is the better book--I find the exposition clearer and the math more rigorous--but Jurafsky and Martin covers more ground and assumes slightly less mathematical background. Regardless, the two books complement each other, so if you're in this field you need both.(less)

This is the standard book on using probabilistic methods to analyze natural language. It has clear discussions of such core areas as N-gram language m...moreThis is the standard book on using probabilistic methods to analyze natural language. It has clear discussions of such core areas as N-gram language modeling, parsing, part of speech tagging, and information retrieval. The exceptionally lucid chapter on Hidden Markov Models is worth the price of the book alone. This is a good starting textbook for newcomers and a useful reference for everyone else. Essential.(less)