Natural Language Processing for the Working Programmer

Post by pdat » Mon, Feb 11, 2013, 5:30 PM UTC

Post by robertfw » Mon, Feb 11, 2013, 5:44 PM UTC

yummyfajitas wrote: post #14

danso wrote: post #11

I'm not that familiar with Haskell and the past week's HN frontpage articles on Monads was just confusing...but what is it about Haskell that makes it more useful for NLP than, say, Python?

Not much. It's a more expressive and cleaner language, but on the other hand python has NLTK + scipy community. Scala (or Java) is another great NLP language. It's got decent libraries (openNLP, mallet, mahout), hadoop, and Scala is almost as nice as Haskell.

Post by nubela » Mon, Feb 11, 2013, 6:21 PM UTC

agibsonccc wrote: post #15

saryant wrote: post #12

Earlier quoted context omitted.

I've used the Stanford NLP library extensively for NER. I made heavy use of it in my senior thesis project. It's pretty straightforward to use their library to read a document and output an XML file containing NER data (and lots of other fun stuff). For instance, from the sentence: > World War II, or the Second World War (often abbreviated as WWII or WW2), was a global military conflict lasting from 1939 to 1945, whi…

For those who want to play around with dynamic output: http://nlp.stanford.edu:8080/parser/ This is a bit more human friendly.

Post by saryant » Mon, Feb 11, 2013, 7:38 PM UTC

narayanb wrote: post #20

saryant wrote: post #12

Earlier quoted context omitted.

I've used the Stanford NLP library extensively for NER. I made heavy use of it in my senior thesis project. It's pretty straightforward to use their library to read a document and output an XML file containing NER data (and lots of other fun stuff). For instance, from the sentence: > World War II, or the Second World War (often abbreviated as WWII or WW2), was a global military conflict lasting from 1939 to 1945, whi…

I had experimented with NLTK, CoreNLP, OpenNLP etc and when it came it NEP extraction, I felt NLTK does the better job (none of them were anywhere close to perfect/dependable), but NLTK had a lot more dictionaries to choose from and overall better. We use a highly customized/overhauled NLTK for our apps Iris(siri for Android) and Friday for Android.

Post by nubela » Mon, Feb 11, 2013, 8:16 PM UTC

eric_bullington wrote: post #10

nubela wrote: post #2

I was working with NLP, and its various toolkits (python-nltk I'm looking at you). The thing about NLP is, there just isn't enough libraries (for humans) to simply plug NLP into use. Even nltk, the premier python library for NLP, seems to be an NLP core-library for building NLP solutions, rather than for building NLP-powered apps. It also seems to extremely unpythonic. Is there a missing link there? I don't know. So…

While it's possible that some parts of NLTK may be unpythonic, I disagree that it's somehow inaccessible or hard to use. The NLTK project is fairly well-documented, and I've never had any difficulty using it. Also, all the NLTK code I've ever examined looks Pythonic to me, unlike the Java-style Python that I sometimes see coming out of academia; they follow PEP8 and have a developer style guide. There may be pockets…