Natural Language Books

Today I rediscovered Rico's book, "Writing the Natural Way" and want to re-read it again. A friend gave it to me in 1984. At that time my mind was in chaos and this book began to help me sort out my thoughts and I wrote alot about personal stuff.
Now in May 2008, it's time to read it again. I'm wanting to write about my life, polio, disability, family, enjoying everyday life. This way of writing is so much easier to write. I remember.
It's time.
Thanks, Linda

This is a monster of a book. I have been using the book for ten years now and evvery time I use the book, I reach further into my creativity. For example, I am writer and a lot of times I hear my left brain, my critic brain, tellng not to write for the day. He tells me to just chill and cool out. I know now that this is the critical factor of the left brain telling me not to work. I learned that from Dr. Gabriel Rico's book. I recommend it highly. It beats using mind altering drugs to contact your right brain, your subconscious.

Lastly, using the book's techniques, you will find that you can easily churn out 1,500 to 2,500 words in two hours. Steven King said his goal is to turn out 1,500 words a day. With this book you can easily do just that and more - like plot, character's dosiers, chapter by chapter breakdown. Only your imagination will limit you.

I recommend this book!

Every language learner knows what it feels like to learn thousands of foreign words and phrases for long years only to be incapable to understand what a native speaker is saying in the end. Mostly it results from the changes that take place when words are put together and their pronunciation become quite different from what is learned in a class, when they are pronounced one at a time. This is the only book I have met that shows it clearly, wasting no time with "unnatural" English and guiding you through the strange phonetics of the ordinary speaker.

This volume is worth it for the opening paper, Steve Abney's brilliant "Statistical methods and linguistics". Reading this paper in Chris Manning's statistical NLP class at CMU changed the way I think about the field. I believe it should be required reading for *linguists*. In my experience, most computational linguists either don't care about mainstream theoretical linguistics, have evaluated it and dismissed it as useless, or have taken on Abney's arguments; the remainder use logic and formal language theory without statistics. I considered myself in that remainder before reading this paper.

Abney argues that Chomsky's original motive for setting up the paradigm of generative grammar though intuited grammaticality judgements was a simple expedient that allowed him to apply the mathematics of his day (automata and formal language theory). Abney dispatches "classical" generative grammar with the finesse that Chomsky showed in dismissing behaviorism. Today, information theory (read Cover and Thomas's excellent book) as applied to natural language (read Manning and Schuetze's excellent book) is the paradigm of choice for the mathematically and computationally savvy linguist.

All in all, anyone who is interested in a scientific approach to linguistics should read Abney's paper.

This book gets applause and 5 stars from me. The artwork is colorful, beckoning each reader to come in and have fun.

The rhyming prose speaks in a child's language, engaging them to think in the form of analogies.

"Gull is to sky as shell is to sand. Child is to family as finger is to hand."

"Water is to wet as towel is to dry. Arm is to swim and wing is to fly."

These are just some of the examples. The sensory detail is rich and inviting. Going on a car journey? What a great game to have your children think of their own analogies.

This book contains a selected papers published in NLP. Papers describe current research in Thesaurus, IR, Multilingual IR and Corpus annotation.

This is a avaliable book for people interested in NLP research.

A very original and well-reasoned text. I'd like to thank Dr. Sproat for his contribution to the field. This is very fine fork.

The book is well-written, easy-to-read, clear. What's that worth for a technical subject? Just about everything. First, it means you can read it like a novel, effortlessly (nearly). Second, you get a clear picture of what he is saying. So the value is there.

With the increasing interest in semantic annotations (RDF and other applications lately advocated by Tim Berners-Lee, the "founder" of the web), it's useful to look at the research literature to see what people have been doing with "conceptual structures" for the past 4 decades.

Since the early days of AI, many scientists have grappled with the issues of knowledge representation. This book and its predecessors cover a conference on exactly that issue. Unlike some other treatments which I find to be either too theoretical or too pragmatic, this one covers just the right level of abstraction and practicality.

I references this and similar works in the design of the semantics annotation systems at Microsoft that will be seen in upcoming products.

I can still remember the excitement I felt back in 1990--my major professor had handed me the paper "Constraint Dependency Grammar" by H. Maruyama, and after reading it is seemed like a whole new world was open. Hard problems seemed to suddently become tractable--it was obvious to us tremendous power and flexibility of representing the process of parsing a sentence as that of constraint satisfaction.

Problem was, the rest of the world viewed the work with a big, collective *yawn*. Dependency grammars were SO passe'--constituency, not dependency, was orthodoxy! Who needs new parsers? Isn't that just re-inventing the wheel? After all, context-free grammars were well-understood and already had very efficient parsers, so why do we need an entirely new grammatical formalism?

About this time it started to be fashionable to induce grammars from corpora. Much effort and money was spent to find ways to learn grammars. Even here, Dependency grammars seemed to have an edge--back in '95 I proved that constraint dependency grammars were PAC-learnable, making them the first grammatical formalism with strictly greater power than context-free grammars to be shown to be learnable. Again, a big collective yawn. Who cares? The whole NLP world was just too busy trying to induce tri-grams and context-free grammars that they didn't pay any attention.

Around 1995 or so, after years of enduring paper rejection after paper rejection, marginallization, and the drying up of research funds, the writing on the wall became quite obvious--the research community just wasn't interested in constraint-based dependency grammars! I dropped out of grad school, went to into VLSI routing, and went on to write several routers which routed the Itanium, Pentium III, IV, and Centrino, and several ARM cores at Intel :-) But I always wondered what might have been....

...well, it looks like what might have been has actually come true! Menzel & his collegues wrote a complete grammar for German as a constraint grammar, which was very influential. Duchier also picked up the contraint grammar formalism and extended it in interesting ways. Fifteen years after Maruyama published his paper, and ten years after I gave the field up for dead, it has suddenly blossomed and spawned an amazing amount of very creative and productive research!

This volume, being the proceedings of a workshop on constraint solving and language processing, shows how this field is absolutely shining with promise and shining with the brillience of the researchers who contribute to the papers gathered herein. Every paper is a gem, but my favorites were:

"An Abductive Treatment of Long-Distannce Dependencies in CHR" by Veronica Dahl. What is interesting here is that Dahl has fused Constraint handling Rules (CHR) from the forefront of the constraint satisfaction community's research with constraint-based parsing, to create a very interesting new parsing system.

"Problems of Inducing Large-Coverage Connstraint-based Dependency Grammars for Czech" by Ondrej Bojar. So-called "crossover constraints," which rule out crossing dependencies, are very useful for grammers like English which have a strict word order. We always hypothesized that constraint based grammars would be useful even for free-word order languages, but apparently not being able to use these crossover constraints presents some problems. The author gives results with Czech, which shows that there is yet more intreseting work to be done in adapting constraint-based formalism for free-word order languges.

"Parsing unrestricted German Text with Defeasible Constraints", by Foth, Daum, and Wolfgang Menzel. Menzel was an early visionary in constraint-based grammar research, and this paper presents very interesting techniques for "relaxing" constraints for parsing eliptical and fragmentary sentences. The WCDG formalism is an extremely promising enhancment to CDG which seems to do a good job of parsing language as its actually spoken--sometimes ungrammatical, sometimes fragmentary.

All-in-all, its very gratifying to see that, 15 years on, Maruyama's initial insights into the usefulness of grammatical formalism based on constraints over dependency graphs is blossoming and bearing fruit.

Yes, a lot has happened since this book was written--statistical grammars, grammar induction, constraint-based grammars, not to mention that whole web thing. No matter. This book is still a valuable stepping stone on the path to NLP nirvana, and everyone who aspires to do research in NLP should come to grips with it.

Why? Because it presents what is really the example par excellance of a unification-based grammar, the core language engine. This is really the first attempt which had any sucess at all to "scale up" nlp techniques to create a system which isn't just another toy. As such, it is one of a very very few descriptions of what it is like to build a BIG program in a logic programming language.

Is this a book which points the way to future reasarch? Well, the authors have pretty much "exhausted the search space" of unification grammars here. Both their potential and their painful limitations have been plummed, and are on display here.

But even though the time of unification grammars has passed, the lessons learned in the construction of the Core Language Engine represent, IMHO, a signature achivement, and real ground gained towards the goal.

Moreover, the spirit of this research lives on. For a bang-up-to-date discussion of where this stream of research has lead, check out Blackburn & Bos's book "Representation and Inference in Natural Language".