size_categories:10K<n<100K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: subcategory
    dtype: string
  - name: code
    dtype: string
  - name: top_category
    dtype: string
  - name: expansion_factor
    dtype: int64
  - name: prompt
    dtype: string
  - name: subtopic
    dtype: string
  - name: subtopic_w_explanation
    dtype: string
  splits:
  - name: train
    num_bytes: 31885923
    num_examples: 34175
  download_size: 5439913
  dataset_size: 31885923
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

This is a list f 34,000 topics based on the BISAC book classification, a standard used to categorize books by subject that is both comprehensive and educationally focused. 
We started with 5,000 topics belonging to 51 categories in [BISAC](https://www.bisg.org/complete-bisac-subject-headings-list) (`top_category` and `subcategory`) and asked Mixtral to generate subtopics for certain topics. 
Below is the final distribution of subtopics in each category (the prompts and generations are available in the dataset):

![image/png](https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/FPSCaK1tBTxQkEHIpxraP.png)
