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---
configs:
- config_name: main
data_files:
- split: train
path: train.jsonl
- split: test
path: test.jsonl
- split: validation
path: val.jsonl
license: apache-2.0
task_categories:
- text-retrieval
language:
- en
source_datasets:
- original
pretty_name: QUEST
annotations_creators:
- wikipedia-sourced
size_categories:
- 1K<n<10K
---
# Dataset Card for QUEST
## Dataset Description
- **Repository: https://github.com/google-research/language/tree/master/language/quest**
- **Paper: https://arxiv.org/abs/2305.11694**
- **Point of Contact: chaitanyamalaviya@gmail.com**
### Dataset Summary
We provide here the data accompanying the paper: [QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations
](https://arxiv.org/abs/2305.11694).
## Dataset Structure
### Data Instances
QUEST contains 6307 training queries, 323 examples for development, and 1727 examples for testing.
### Data Fields
Each examples file contains newline-separated json dictionaries with the following fields:
* `query` - Paraphrased query written by annotators.
* `docs` - List of relevant document titles.
* `original_query` - The original query which was paraphrased. Atomic queries are
enclosed by `<mark></mark>`. Augmented queries do not have this field populated.
* `scores` - This field is not populated and only used when producing predictions to enable sharing the same data structure.
* `metadata` - A dictionary with the following fields:
* `template` - The template used to create the query.
* `domain` - The domain to which the query belongs.
* `fluency` - List of fluency ratings for the query.
* `meaning` - List of ratings for whether the paraphrased query meaning is the
same as the original query.
* `naturalness` - List of naturalness ratings for the query.
* `relevance_ratings` - Dictionary mapping document titles to relevance ratings
for the document.
* `evidence_ratings` - Dictionary mapping document titles to evidence ratings
for the document.
* `attributions` - Dictionary mapping a document title to its attributions
attributions are a list of dictionaries mapping a query substring to a
document substring.
The document corpus is at https://storage.googleapis.com/gresearch/quest/documents.jsonl. Note that this file is quite large
(899MB). The format is newline separated json dicts containing `title` and
`text`.
### Citation Information
```
@inproceedings{malaviya23expertqa,
title = {QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations},
author = {Chaitanya Malaviya and Peter Shaw and Ming-Wei Chang and Kenton Lee and Kristina Toutanova},
booktitle = {ACL},
year = {2023},
url = "https://arxiv.org/abs/2305.11694"
}
```
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