Resources

[dariusk]

This is an open issue where you can comment and add resources that might come in handy for NaNoGenMo.

There are already a ton of resources on the old resources thread for the 2013 edition.

[aparrish]

Use ConceptNet to start writing your own Tale-Spin-like stories. "There was a kitten. The kitten was someone's pet. The kitten wanted to explore. Surfing the web is used for exploring. You need to connect to the internet in order to surf the web."

[aparrish]

I also feel like there may be relevant things in Michael Cook's list of procedural generation tutorials.

[enkiv2]

I recommend, in addition to ConceptNet, CMU NELL. It's another ontology
project, this time generated by parsing some web pages. The data sets are
here: http://rtw.ml.cmu.edu/rtw/resources

(There's also the potential for some of us to use IBM Watson, probably. I
don't have that resource, but now that the APIs are open for some
definition of open, somebody could use them creatively I suppose)

On Mon, Oct 20, 2014 at 1:09 PM, Allison Parrish notifications@github.com
wrote:

I also feel like there may be relevant things in Michael Cook's list of
procedural generation tutorials
http://procjam.tumblr.com/post/99689402659/procedural-generation-tutorials-getting-started
.

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[cpressey]

Project Gutenberg is now being mirrored on Github -- https://github.com/GITenberg -- although exactly what benefit that may or may not bring to you, the potential NaNoGenMo participant, I cannot say. I mention it mainly because I'm not sure if it was around last time -- I only noticed it recently (a month or two ago.)

[tullyhansen]

Generate a sufficiently complicated graph, and then explicate it for 50,000 words with wordgraph? https://wordgraph.readthedocs.org/en/latest/

[ikarth]

http://www.ark.cs.cmu.edu/TweetNLP/
I came across this today: Tweet NLP

We provide a tokenizer, a part-of-speech tagger, hierarchical word clusters, and a dependency parser for tweets, along with annotated corpora and web-based annotation tools.

[jeffThompson]

Got a postcard from Blurb yesterday: if you want to print your finished novel, get 20% off using the code HOLIDAY14.

Expires November 30, so you'll have to finish a little early...

[swizzard]

2nding Tweet NLP--I'm doing some twitter-related stuff, and hacked around on it via Clojure for a bit last night. It's not terribly well-documented outside command-line stuff, but the source code is clear and well-commented.

I also can't recommend NLTK strongly enough. It's definitely intimidating if you're not familiar with NLP, but that's mostly because it's got so much stuffed into it--wordnet, several phenomenal corpora (including a bunch of Project Gutenberg stuff), markov generators, & more. NLTK3 is even Py3K-compatible, for all of you who really want to put some unicode in your novels/hate print statements.

[christiaanw]

2nding @swizzard about NLTK (though I just uninstalled NLTK3 in favor of 2.04 because Markov generators are not included in NLTK3), and adding Pattern to the mix. Pattern has linguistics (for parsing and information extraction based on chunk/word patterns), web-search (Google, Bing, Yahoo, Twitter, Wikipedia), web-crawling, language modelling (TF-IDF), classification, and commonsense reasoning. They're pretty approachable using the included examples. The website has some usage examples. patent-generator uses the search module from Pattern to generate patents from literary texts.

On the literary side I would like to mention two resources on Ubuweb: It's Anthology of Conceptual Writing and /ubu editions. There's The first thousand numbers classified in alphabetical order by Claude Closky, Name, A Novel by Toadex Hobgrammathon and All the Numbers from Numbers by Kenneth Goldsmith, and possibly more stuff which could have (or has) been been done by computer.

[swizzard]

I had no idea they'd taken Markov generators out of NLTK3! That's such a bummer.

Pattern sounds great though. I'll definitely be looking into it.

[hugovk]

What's a good way to create a PDF book from plain text?

Are there any handy (Python) scripts to generate a half-decent PDF by throwing a bunch of text at it?

Or is it better to export to PDF from Libre/Open Office?

[cpressey]

@hugovk This is a biased opinion of course, but I like http://johnmacfarlane.net/pandoc/ for document format conversions. It's written in Haskell, which may or may not be your cup of tea, but you can shell it out from Python. I'm sure there are Python-specific tools for generating PDFs too (generating a PDF is actually not that difficult, especially if it's just text no images,) but I don't know any offhand.

[jeffThompson]

@hugovk – I've tried, with limited success, to use ReportLab. It's very confusing and hard to get nice formatting.

I would suggest generating a .txt file, then using Word/InDesign to format and export, or Ghostscript on the command line, or called from Python at the end of your script.

[dariusk]

@hugovk, Consider generating markup instead of text. I typically generate html, open it in a browser, and then use the print to PDF function.

This time around I might generate LaTeX markup instead, which renders very nicely to PDF.

[tullyhansen]

@hugovk Seconding Darius on LaTex - my preferred intermediary format from plain text is Fletcher Penney's MultiMarkdown, which is reasonably painless once up and running. Happy to help if I can!