/gutenberg-poetry-corpus

A corpus of poetry from Project Gutenberg

Primary LanguageJupyter Notebook

A Gutenberg Poetry Corpus

By Allison Parrish

This is a Gutenberg Poetry corpus, comprised of approximately three million lines of poetry extracted from hundreds of books from Project Gutenberg. The corpus is especially suited to applications in creative computational poetic text generation.

Download the corpus here.

How to use it

The corpus is provided as a gzipped newline-delimited JSON format. Here's a representative excerpt:

{"s": "The Heav'ns and all the Constellations rung,", "gid": "20"}
{"s": "The Planets in thir stations list'ning stood,", "gid": "20"}
{"s": "While the bright Pomp ascended jubilant.", "gid": "20"}
{"s": "Open, ye everlasting Gates, they sung,", "gid": "20"}
{"s": "Open, ye Heav'ns, your living dores; let in", "gid": "20"}

Each line of poetry is represented by a JSON object, with one object per line in the archive. The value for the s key is the line of poetry itself, and the value for the gid key is the ID of the Project Gutenberg book that the line comes from. You can use the value for gid to look up the title and author of the book that serves as that line's source, either "by hand" (just type the ID into Project Gutenberg's search box) or using a computer-readable version of the Project Gutenberg metadata (such as Gutenberg, dammit).

The Quick Experiments notebook included in this repository shows how to get up and running quickly with the corpus in Python. No need to install the Python module in this repository---working with the data is surprisingly straightforward!

How it was made

The corpus was generated using the included build.py script, which uses Gutenberg, dammit to provide access to books from Project Gutenberg. First, books with the string poetry listed in their "Subject" metadata are added to a list. Then, the plaintext versions of those books are scanned for lines that "look like" poetry, based on a set of textual characteristics, such as their length and capitalization. (See build.py for a list of these characteristics.) Finally, lines are compared against a word list (from wordfilter) to exclude lines that may contain egregiously offensive content.

NOTE: While a best-effort attempt has been made to exclude offensive language from this corpus, I have not personally vetted each of the three million lines. If you use this corpus to produce work for the public, please read over it first or take approriate measures to ensure that the language in the work is appropriate for you and your audience.read over it first or take approriate measures to ensure that the language in the work is appropriate for you and your audience.

The corpus contains only lines of poetry from books that the Project Gutenberg metadata identifies as being written in English and as being free from copyright (i.e., public domain) in the United States.

Examples of usage

Previous versions of this corpus have served as a foundation for several projects produced by myself and others:

If you make something cool with this corpus, let me know!

Build your own from scratch

You don't need to read any of the following if you just want to use the corpus. If you're interested in building your own version from scratch, read on.

This repository includes a script to build the Gutenberg Poetry corpus from the files included in Gutenberg, dammit. First, download the Gutenberg, dammit archive. Then install this package, like so:

pip install --process-dependency-links https://github.com/aparrish/gutenberg-poetry-corpus/archive/master.zip

You can then run the following command to produce your own version of the corpus:

python -m gutenbergpoetrycorpus.build --srczip=PATH-TO-GUTENBERG-DAMMIT-ZIP | gzip -c >gutenberg-poetry.ndjson.gz

Parameters for what gets included in the corpus can be adjusted in build.py. (E.g., it should be relatively easy to adapt this script to produce corpora of poetry in different languages!)

License

To the best of my knowledge, the Gutenberg Poetry corpus contains only text excerpted from works that are is in the public domain (at least in the United States). For avoidance of doubt, I release the particular arrangement of these excerpts in the provided format as CC0.

The code in this repository is provided under the following license:

Copyright 2018 Allison Parrish

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