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--- |
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license: openrail |
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language: |
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- fr |
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tags: |
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- french |
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- philosophy |
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- quebec |
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size_categories: |
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- 100K<n<1M |
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--- |
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# Dataset Card for Dataset Name |
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## Dataset Description |
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### Dataset Summary |
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This dataset contains all french philosophy that has been published on erudit.org. It has been generated using a Bs4 web parser that you can find in this repo: https://github.com/MFGiguere/french-philosophy-generator. |
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### Supported Tasks and Leaderboards |
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This dataset could be useful for this (non-exhaustive) set of tasks: detect if a text is philosophical or not, generate philosophical sentences, generate an abstract from an article, ... |
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### Languages |
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The database includes includes all journals where the main language is french but might include non-french sentences from quotes or special editions. |
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## Dataset Structure |
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### Data Instances |
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Each row of the databse is a sentence and each column is a text's metadata. |
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### Data Fields |
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The data is structured as follow, which makes it possible to combine sentences into paragraphs, sections or whole texts. |
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``` |
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features = { |
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"Journal": str, #The name of the journal where the text was published |
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"Author": str, #Required to be able to generate texts by author. |
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"Year": str, #Will help form a sense of direction on a large scale. |
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"Title": str, #Can be useful for smaller dataset, but can be inferred with enough files. |
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"section_rank": int, #Abstract will be 0 and sections will start as 1. |
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"par_rank": int, #Abstract will be 0 and paragraphs will start as 1. |
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"sent_rank": int, #no of sentence in the paragraph |
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"text": str #Will be single sentence at a time. |
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} |
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``` |
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## Additional Information |
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### Contributions |
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This dataset exists because of the Deepmay 2023 bootcamp instructors who gave us a solid instruction to language models and a friend at the Bootcamp that suggested me to host this dataset publicly on here! |
