31–35 of 35 posts
Probably up there amongst the most useful Python libraries IMO. Hasn't it been available for free online for a long time now though? Anyway, in case anyone reading this missed it, the Stanford NLP class taught by Chris Manning and Dan Jurafsky starting next week (Jan 23rd) will allow programming assignments to be submitted using Python and NLTK, which is really good news. So now's a good time to get familiar with the…
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The Language Instinct is a great book, but unless the content of newer editions has changed significantly, it's more of an overview of linguistics in general, and language acquisition in particular. There's not much -- if any -- practical NLP. For example, looking at Amazon's statistically-improbable phrases (SIPs), I see nothing related to NLP, nor do I see any terms related to practical NLP during a quick glance of…
Oh no, I didn't intend for The Language Instinct as an introduction to NLP, but as a basic introduction to the fundamentals of linguistics. I mainly had in mind terms like morpheme, phoneme, scope, etc. A basic understanding of these concepts will make reading the NLTK book much easier, although it isn't necessary.
LinkGrammar: http://www.link.cs.cmu.edu/link/ is the other NLP tool kit in python, may be suited for use by those who might be intimidated by the need to write their own grammar. It is integrated into and maintained by the authors of Abiword. There is a talk on this other library at Pycon, this year: https://us.pycon.org/2012/schedule/presentation/187/
LinkGrammar is not really a toolkit and it is not written in Python. It is written in C.
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> I'm not sure that any book on the NLTK could avoid the concepts you're referring to. Me too. I'm saying the book (like almost all technical documentation) should be task-based. Let people read the chapter with their problem - don't ask them to read a whole list of solutions to work out which one is applicable. Eg: - Title: Preparing Text for Analysis (explain what tokenizing is and why it's necessary) - Title: 'gau…
Thanks for your response. Can you give me an example of how you would frame the material in your response using task-based documentation? It seems to me that the NLTK book does exactly what you're describing in most sections, but perhaps if you gave a counterexample I would better understand.
My response is task based. The titles are tasks you would like to perform.
Compare with the TOC of the NLTK book:
'Accessing Text Corpora and Lexical Resources (extras)'
What is this? What does it help me do?
If it's prepare a document for analysis, then the title should be 'Preparing text for analysis'
'3. Processing Raw Text'
'Process' is a meaningless word, like 'System' or 'Data'
4. Writing Structured Programs (extras)
That sounds like a coding guidelines document. What does it have to do with language? Why do I want to do this?
7. Extracting Information from Text
Better.
8. Analyzing Sentence Structure (extras) 9. Building Feature Based Grammars
Why do I want to do that?
10. Analyzing the Meaning of Sentences (extras)
Good. Better would be 'Determining the meaning of sentences'
11. Managing Linguistic Data
'Managing' is another meaningless word. Are you going to process a managed data system now? No? Perhaps there's some practical advice regarding handling large volumes of text here. Cool, then my task, and the title, should be 'Handing large volumes of text'.
Earlier quoted context omitted.
> I'm not sure that any book on the NLTK could avoid the concepts you're referring to. Me too. I'm saying the book (like almost all technical documentation) should be task-based. Let people read the chapter with their problem - don't ask them to read a whole list of solutions to work out which one is applicable. Eg: - Title: Preparing Text for Analysis (explain what tokenizing is and why it's necessary) - Title: 'gau…
Thanks for your response. Can you give me an example of how you would frame the material in your response using task-based documentation? It seems to me that the NLTK book does exactly what you're describing in most sections, but perhaps if you gave a counterexample I would better understand.