By Allison Parrish

This is the source code for my NaNoGenMo 2015 project. It's written in Python 2.7. It makes extensive use of spaCy (for parsing English sentences) and Pattern's WordNet module.

Here's a PDF with output from this procedure.

The source code is not in great shape. Apologies for that. :/

The gen.py script can be run at the command-line to fill in the template.tex file with chapters and paragraphs filled in.

$ export SPACY_DATA=/path/to/your/spacy/data
$ python gen.py 300 nature_sentences.txt <template.tex >output.tex

You can replace 300 with the number of chapters you want to generate. The text output from the program is a LaTeX file that you can convert to PDF using your regular LaTeX toolchain.

For Python dependencies, see requirements.txt.

I included the database of extracted sentences in the repository as nature_sentences.txt. If you want to extract the sentences yourself, you'll need to have the Project Gutenberg corpus on your computer.

I was working with the Project Gutenberg files from the April 2010 DVD ISO. You can download it here; make sure it's mounted as /Volumes/PGDVD_2010_04_RC2/. For metadata, I was using Leonard Richardson's 47000_metadata.json (which the Python scripts expect to be available in the working directory).

A quick outline of what's in all of the files...

• extract.py: various functions for extracting/replacing grammatical consituents in English sentences using spaCy; also most of the WordNet shenanigans
• extract_nature_sentences.py: command-line script to extract "natural" sentences from the Project Gutenberg corpus
• gen.py: functions and classes for generating chapters, paragraphs and sentences from the nature sentences corpus (including the paragraph model)
• gutenfetch.py: functions for searching Gutenberg metadata and retrieving text from the mounted Project Gutenberg ISO image
• nature_sentences.txt: pre-extracted corpus of sentences having no references to humans and whose subjects are all natural objects/phenomena
• test.py: unit/integration tests for a lot of the spaCy functions
• test_wordnet.py: unit tests for WordNet functions

Copyright (c) 2015 Allison Parrish

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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