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Soiled Secrets and techniques of BookCorpus, a Key Dataset in Machine Studying | by Jack Bandy

Soiled Secrets and techniques of BookCorpus, a Key Dataset in Machine Studying | by Jack Bandy

2023-09-19 07:13:17

A better take a look at BookCorpus, the textual content dataset that helps practice massive language fashions for Google, OpenAI, Amazon, and others

Picture by Javier Quiroga on Unsplash

BookCorpus has helped practice at the very least thirty influential language fashions (together with Google’s BERT, OpenAI’s GPT, and Amazon’s Bort), in line with HuggingFace.

However what precisely is inside BookCorpus?

That is the analysis query that Nicholas Vincent and I ask in a new working paper that makes an attempt to handle among the “documentation debt” in machine studying analysis — an idea mentioned by Dr. Emily M. Bender and Dr. Timnit Gebru et al. of their Stochastic Parrots paper.

Whereas many researchers have used BookCorpus because it was first launched, documentation stays sparse. The original paper that launched the dataset described it as a “corpus of 11,038 books from the online,” and offered six abstract statistics (74 Million sentences, 984 Million phrases, and so forth.).

We determined to take a better look — here’s what we discovered.

For context, it’s first necessary to notice that BookCorpus accommodates a pattern of books from, an internet site that describes itself as “the world’s largest distributor of indie ebooks.”

As of 2014, Smashwords hosted 336,400 books. For comparability, in the identical yr, the Library of Congress housed a complete of 23,592,066 catalogued books (about seventy occasions as many).

The researchers who collected BookCorpus downloaded each free ebook longer than 20,000 phrases, which resulted in 11,038 books — a 3% pattern of all books on However as mentioned beneath, we discovered that hundreds of those books have been duplicates and solely 7,185 have been distinctive, so actually BookCorpus is just a 2% pattern of all books on Smashwords.

Within the full datasheet, we offer details about funding (Google and Samsung have been among the many funding sources), the unique use case for BookCorpus (sentence embedding), in addition to different particulars outlined within the datasheet standard. For this weblog put up, I’ll spotlight among the extra regarding findings.

???????? Copyright Violations

In 2016, Richard Lea explained in The Guardian that Google didn’t search consent from authors in BookCorpus, whose books assist energy Google’s applied sciences.

Going even additional, we discover proof that BookCorpus instantly violated copyright restrictions for a whole lot of books that ought to not have been redistributed by way of a free dataset. For instance, over 200 books in BookCorpus explicitly state that they “is probably not reproduced, copied and distributed for industrial or non-commercial functions.”

We additionally discover that at the very least 406 books included within the free BookCorpus dataset now value cash on Smashwords, the dataset’s supply. To buy these 406 books would value $1,182.21 as of April 2021.

???????? Duplicate Books

BookCorpus is usually described as containing 11,038 books, which is what the unique authors report. Nevertheless, we discovered that hundreds of books have been duplicates, and actually solely 7,185 books within the dataset are distinctive. The precise breakdown is as follows:

  • 4,255 books occurred as soon as (i.e. weren’t duplicated)
  • 2,101 books occurred twice ????????
  • 741 books occurred thrice ????????????
  • 82 books occurred 4 occasions ????????????????
  • 6 books occurred 5 occasions ????????????????????

???? Skewed Style Illustration

In comparison with a brand new model known as BookCorpusOpen, and one other dataset of all of the books on Smashwords (Smashwords21), the unique BookCorpus has some vital style skews. Here’s a desk with all the main points:

Notably, BookCorpus over-represents the Romance style, which isn’t essentially shocking given broader patterns in self-publishing (authors consistently find that romance novels are in high demand). It additionally accommodates fairly a number of books within the Vampires style, which can have been phased out on condition that no vampire books seem in Smashwords21.

In and of itself, skewed illustration can result in points when coaching massive language fashions. However as we checked out some “romance” novels, it grew to become clear that some books pose additional issues.

???? Problematic Content material

Whereas there may be extra work to be achieved in figuring out the extent of problematic content material in BookCorpus, our evaluation exhibits that it positively exists. Think about, for instance, one novel in BookCorpus known as The Cop And The Girl From The Coffee Shop.

The ebook’s preamble clearly states that “the fabric on this ebook is meant for ages 18+.” On Smashwords, the ebook’s tags embody “alpha male” and “submissive feminine.”

Whereas there could also be little hurt from knowledgeable adults studying a ebook like this, feeding it as coaching materials to language fashions would contribute to well-documented gender discrimination in these applied sciences.

See Also

???? Doubtlessly Skewed Non secular Illustration

With regards to discrimination, the recently-introduced BOLD framework additionally suggests taking a look at seven of the commonest religions on this planet: Sikhism, Judaism, Islam, Hinduism, Christianity, Buddhism, and Atheism.

Whereas we don’t but have the suitable metadata to totally analyze non secular illustration in BookCorpus, we did discover that BookCorpusOpen and Smashwords21 exhibit skews, suggesting that this may be a difficulty within the authentic BookCorpus dataset. Right here is the breakdown:

Extra work is required to make clear non secular illustration within the authentic model of BookCorpus, nonetheless, BookCorpus does use the identical supply as BookCorpusOpen and Smashwords21, so related skews are seemingly.

⚖️ Lopsided Creator Contributions

One other potential challenge is lopsided writer contributions. Once more, we don’t but have all of the metadata we would wish for an entire evaluation of BookCorpus, however we will make estimates based mostly on our Smashwords21 dataset.

In Smashwords21, we discovered that writer contributions have been fairly lopsided, with the highest 10% of authors contributing 59% of all phrases within the dataset. Phrase contributions roughly comply with the Pareto principle (i.e. the 80/20 rule), with the highest 20% of authors contributing 75% of all phrases.

Equally, by way of ebook contributions, the highest 10% of authors contributed 43% of all books. We even discovered some “super-authors,” like Kenneth Kee, who has printed over 800 books.

If BookCorpus appears in any respect just like as a complete, then a majority of books within the dataset have been most likely written by a minority of authors. In lots of contexts, researchers could wish to account for these lopsided contributions when utilizing the dataset.

With new NeurIPS standards for dataset documentation and even a complete new track devoted to datasets, hopefully the necessity for retrospective documentation efforts (just like the one offered right here) will decline.

Within the meantime, efforts like this one might help us perceive and enhance the datasets that energy machine studying.

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