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---
license: mit
tags:
- natural-language-understanding
language_creators:
- expert-generated
- machine-generated
language:
- en
multilinguality:
- multilingual
pretty_name: Fact Completion Benchmark for Text Models
size_categories:
- 100K<n<1M
task_categories:
- text-generation
- fill-mask
- text2text-generation
task_ids:
- fact-checking
---
# Dataset Card for Fact_Completion

## Dataset Description

- **Homepage:** https://bit.ly/ischool-berkeley-capstone
- **Repository:** https://github.com/daniel-furman/Capstone
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** Daniel Furman (daniel_furman@berkeley.edu)

### Dataset Summary

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

```
@misc{calibragpt,
  author = {Shreshta Bhat and Daniel Furman and Tim Schott},
  title = {CalibraGPT: The Search for (Mis)Information in Large Language Models},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/daniel-furman/Capstone}},
}
```

```
@misc{dong2022calibrating,
      doi = {10.48550/arXiv.2210.03329},
      title={Calibrating Factual Knowledge in Pretrained Language Models}, 
      author={Qingxiu Dong and Damai Dai and Yifan Song and Jingjing Xu and Zhifang Sui and Lei Li},
      year={2022},
      eprint={2210.03329},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

```
@misc{meng2022massediting,
      doi = {10.48550/arXiv.2210.07229},
      title={Mass-Editing Memory in a Transformer}, 
      author={Kevin Meng and Arnab Sen Sharma and Alex Andonian and Yonatan Belinkov and David Bau},
      year={2022},
      eprint={2210.07229},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

### Contributions

[More Information Needed]