https://github.com/datascienceuibk/chroniclingamericaqa
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper Pages
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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✓DOI references
Found 6 DOI reference(s) in README -
✓Academic publication links
Links to: acm.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.9%) to scientific vocabulary
Repository
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper Pages
Basic Info
Statistics
- Stars: 10
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper Pages
ChroniclingAmetricaQA, is a large-scale question-answering dataset comprising question-answer pairs over a collection of historical American newspapers to facilitate the development of QA and MRC systems over historical texts.
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Dataset
Structured as JSON files, the ChricinclingAmericaQA dataset includes train.json, dev.json, and test.json for training, validation, and testing phases, respectively.
- Data Structure: ```json [ { "queryid": "", "question": "", "answer": "", "organswer": "", "paraid": "", "context": "", "rawocr": "", "publicationdate": "", "transque": "", "trans_ans": "", "url": "" } ]
```
Dataset Statistics
| | Training | Development | Test | | ----------------- | --------- | ----------- | ------ | | Num. of Questions | 439,302 | 24,111 | 24,084 |
Citation
If you find the dataset helpful, please consider citing our paper.
@inproceedings{10.1145/3626772.3657891,
author = {Piryani, Bhawna and Mozafari, Jamshid and Jatowt, Adam},
title = {ChroniclingAmericaQA: A Large-scale Question Answering Dataset based on Historical American Newspaper Pages},
year = {2024},
isbn = {9798400704314},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3626772.3657891},
doi = {10.1145/3626772.3657891},
booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {2038–2048},
numpages = {11},
keywords = {heritage collections, ocr text, question answering},
location = {Washington DC, USA},
series = {SIGIR '24}
}
License
This project is licensed under the MIT License - see the LICENSE file for details.
Owner
- Name: DataScienceUIBK
- Login: DataScienceUIBK
- Kind: organization
- Repositories: 1
- Profile: https://github.com/DataScienceUIBK
GitHub Events
Total
- Issues event: 2
- Watch event: 5
- Issue comment event: 4
- Push event: 2
Last Year
- Issues event: 2
- Watch event: 5
- Issue comment event: 4
- Push event: 2