In this study, we manually labeled 8,162 open-domain questions as temporally ambiguous or unambiguous, creating ⬇️TempAmbiQA. You can access and download the dataset by clicking on the corresponding link.
[
{
"question": "",
"is_ambiguous": ,
}
]
The statistics of the dataset are given below:
No. of Questions | |
---|---|
#Questions | 8,162 |
Ambiguous Questions | 3,879 |
Unambiguous Questions | 4,283 |
Average Question Length (Words) | 8.55 |
This project is licensed under the MIT License - see the LICENSE file for details.
If you find this work useful, please cite 📜our paper:
Bhawna Piryani, Abdelrahman Abdallah, Jamshid Mozafari, and Adam Jatowt. 2024. Detecting Temporal Ambiguity in Questions. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 9620–9634, Miami, Florida, USA. Association for Computational Linguistics.
@inproceedings{piryani-etal-2024-detecting,
title = "Detecting Temporal Ambiguity in Questions",
author = "Piryani, Bhawna and
Abdallah, Abdelrahman and
Mozafari, Jamshid and
Jatowt, Adam",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.562",
pages = "9620--9634",
}
Thanks to our contributors and the University of Innsbruck for supporting this project.