https://github.com/amazon-science/street-reasoning
STREET: a multi-task and multi-step reasoning dataset
Science Score: 26.0%
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
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○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 (6.2%) to scientific vocabulary
Repository
STREET: a multi-task and multi-step reasoning dataset
Basic Info
Statistics
- Stars: 22
- Watchers: 3
- Forks: 4
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
STREET: a Multi-Task Structured Reasoning and Explanation Benchmark

Running Geneartion Script
This repository contains the annotations and script to generate the data for the STREET dataset.
Requirements:
- Python 3
Execute the following python script:
python run_street_data_generation.py
The script will download some of the original datasets in which STREET is built and merge them with our reasoning and explanation annotations.
The final data will be contained within the ./data/$STREET_TASK$/reasoning_annotated_$SPLIT$.jsonl files in JSONL format.
Citation
@inproceedings{
ribeiro2023street,
title={{STREET}: A {MULTI}-{TASK} {STRUCTURED} {REASONING} {AND} {EXPLANATION} {BENCHMARK}},
author={Danilo Neves Ribeiro and Shen Wang and Xiaofei Ma and Henghui Zhu and Rui Dong and Deguang Kong and Juliette Burger and Anjelica Ramos and zhiheng huang and William Yang Wang and George Karypis and Bing Xiang and Dan Roth},
booktitle={International Conference on Learning Representations},
year={2023},
url={https://openreview.net/forum?id=1C_kSW1-k0}
}
Owner
- Name: Amazon Science
- Login: amazon-science
- Kind: organization
- Website: https://amazon.science
- Twitter: AmazonScience
- Repositories: 80
- Profile: https://github.com/amazon-science
GitHub Events
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Last Year
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Past Year
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Top Authors
Issue Authors
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