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---
dataset_info:
features:
- name: text_id
dtype: string
- name: page_url
dtype: string
- name: page_title
dtype: string
- name: section_title
dtype: string
- name: context_page_description
dtype: string
- name: context_section_description
dtype: string
- name: media
sequence: string
- name: hierachy
sequence: string
- name: category
sequence: string
- name: source_id
dtype: string
splits:
- name: train
num_bytes: 14378574060.336058
num_examples: 10134744
download_size: 6408012391
dataset_size: 14378574060.336058
license: cc-by-sa-4.0
size_categories:
- 100M<n<1B
---
# Dataset Card for "AToMiC-Texts-Mapped"
## Dataset Description
- **Homepage:** [AToMiC homepage](https://trec-atomic.github.io/)
- **Source:** [WIT](https://github.com/google-research-datasets/wit)
- **Paper:** [WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning](https://arxiv.org/abs/2103.01913)
### Languages
This dataset only contains English in Wikipedia (parsed from the 20221101 XML dump).
### Data Instances
Each instance is a section of a Wikipedia page. We also provide its page-level information, and associated information such as categories and media.
The `source_id` can be mapped back to the instance in the original [WIT instance](https://github.com/google-research-datasets/wit/blob/main/DATA.md).
Notice that the WIT dataset is crawled from the earlier version of Wikipedia (2020-08-30).
The WIT dataset is mapped to the new dump by pure BM25 matching with [Anserini](https://github.com/castorini/anserini).
### Intended Usage
1. Text collection for Image-to-Text retrieval
2. Language model pretraining
3. Document classification
### Licensing Information
[CC BY-SA 4.0 international license](https://creativecommons.org/licenses/by-sa/4.0/)
### Citation Information
TBA
### Acknowledgement
Thanks to:
[mwparserfromhell](https://github.com/earwig/mwparserfromhell)
[Datasets](https://github.com/huggingface/datasets)
[Anserini](https://github.com/castorini/anserini)
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)