| | --- |
| | license: cc-by-sa-3.0 |
| | language: |
| | - en |
| | tags: |
| | - wiki |
| | - training |
| | task_categories: |
| | - text-classification |
| | - text-generation |
| | pretty_name: Fandom23K Wikis |
| | size_categories: |
| | - 10M<n<100M |
| | --- |
| | |
| | # Dataset Card for Fandom23K |
| |
|
| | *The BigKnow2022 dataset and its subsets are not yet complete. Not all information here may be accurate or accessible.* |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** (TODO) https://docs.ryokoai.com/docs/training/dataset#Fandom22K |
| | - **Repository:** <https://github.com/RyokoAI/BigKnow2022> |
| | - **Paper:** N/A |
| | - **Leaderboard:** N/A |
| | - **Point of Contact:** Ronsor/undeleted <ronsor@ronsor.com> |
| |
|
| | ### Dataset Summary |
| |
|
| | Fandom23K is a dataset composed of 15,616,749 articles scraped from approximately 23,665 Fandom.com wikis between March 14 and March 18, 2023. |
| | It is a subset of the upcoming BigKnow2022 dataset. |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | This dataset is primarily intended for unsupervised training of text generation models; however, it may be useful for other purposes. |
| |
|
| | * text-classification |
| |
|
| | ### Languages |
| |
|
| | * English |
| | * Potentially other languages in much smaller quantities. |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Instances |
| |
|
| | ```json |
| | { |
| | "tag": "fandom.wikia2011", |
| | "text": "# Add Your Wiki's Highlights\n\nWrite the text of your article here!-_-\n\n", |
| | "title": "Add Your Wiki's Highlights" |
| | } |
| | { |
| | "tag": "fandom.wikia2011", |
| | "text": "# Add Your Wiki's Highlights!\n\nWikia wants to hear from you! What significant milestones did your wiki experience in 2011? What cool things did the community try out?\nCreate a page for the wiki you're most active on! Be sure to add it to the Entertainment, Gaming, or Lifestyle categories so it shows up in the right place!\n\n", |
| | "title": "Add Your Wiki's Highlights!" |
| | } |
| | { |
| | "tag": "fandom.wikia2011", |
| | "text": "# Assassins Creed Wiki 2011\n\nIn 2011, Assassin's Creed Wiki tested new Wikia features such as Message Wall, Chat, and New Layouts.\n\n", |
| | "title": "Assassins Creed Wiki 2011" |
| | } |
| | ``` |
| |
|
| | ### Data Fields |
| |
|
| | * **text**: the actual article text |
| | * **title**: the article title |
| | * **tag**: text source tag, in the following format: `fandom.<wiki name>` |
| |
|
| | ### Data Splits |
| |
|
| | No splitting of the data was performed. |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | Fandom23K provides an up-to-date corpus containing pop culture and media information spanning a variety of interests and |
| | hobbies. Previous datasets containing such information are either part of a large and harder-to-handle whole, such as |
| | Common Crawl, do not provide enough variety, or are simply outdated. |
| |
|
| | ### Source Data |
| |
|
| | #### Initial Data Collection and Normalization |
| |
|
| | *More information about any referenced scripts, commands, or programs used may be found in the BigKnow2022 GitHub repository.* |
| |
|
| | First, a list of active Fandom wikis was gathered into a text file. Active is defined as "having at least 250 images on the wiki." |
| | This list was gathered in early January 2023, despite the actual wiki content being more recent. |
| |
|
| | Second, the `scrape_fandom.py` script was used to generate and download an up to date dump for each of the wikis. |
| |
|
| | Third, `wikiextractor` was used to process these dumps into single XML files containing each article stripped of all formatting |
| | besides links. |
| |
|
| | Fourth, `dump2jsonl` was used to convert the XML files into JSONL files with an article per line. Light markdown formatting was |
| | applied, converting the HTML links to markdown-formatted links, and automatically making the article's title a header. |
| |
|
| | Finally, the JSONL files were concatenated into the Fandom23K dataset. The version uploaded to this repository, however, is split |
| | into multiple files, numbered 00 through 04 inclusive. |
| |
|
| | #### Who are the source language producers? |
| |
|
| | The contributors of each wiki. |
| |
|
| | ### Annotations |
| |
|
| | #### Annotation process |
| |
|
| | Wiki names and article titles were collected alongside the article text. Other than that automated process, no annotation was performed. |
| |
|
| | #### Who are the annotators? |
| |
|
| | There were no human annotators. |
| |
|
| | ### Personal and Sensitive Information |
| |
|
| | The dataset was collected from public wiki data. As a result, we do not believe |
| | it should contain any PII and did not inspect it further. |
| |
|
| | ## Considerations for Using the Data |
| |
|
| | ### Social Impact of Dataset |
| |
|
| | This dataset is intended to be useful for anyone who wishes to train a model to generate "more entertaining" content requiring |
| | knowledge of popular culture or a particular niche. |
| |
|
| | ### Discussion of Biases |
| |
|
| | This dataset contains text from random Internet users and generally should not be used as an authoritative source of information. |
| | Additionally, this dataset was not filtered at all. We recommmend its usage for research purposes only. |
| |
|
| | ### Other Known Limitations |
| |
|
| | This dataset is based on a list of active wikis from January 2023, even though the actual wiki content may be more recent. Additionally, |
| | smaller yet still active wikis may have been excluded. |
| |
|
| | ## Additional Information |
| |
|
| | ### Dataset Curators |
| |
|
| | Ronsor Labs |
| |
|
| | ### Licensing Information |
| |
|
| | CC-BY-SA 3.0, except for any portions which state otherwise. |
| |
|
| | ### Citation Information |
| |
|
| | ``` |
| | @misc{ryokoai2023-bigknow2022, |
| | title = {BigKnow2022: Bringing Language Models Up to Speed}, |
| | author = {Ronsor}, |
| | year = {2023}, |
| | howpublished = {\url{https://github.com/RyokoAI/BigKnow2022}}, |
| | } |
| | ``` |
| |
|
| | ### Contributions |
| |
|
| | Thanks to @ronsor for gathering this dataset. |
| |
|
