metadata

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 .

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"
}