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Datasets:
nlpkevinl
/
whatsthatbook

Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
ArXiv:
Libraries:
Datasets
pandas
License:
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Dataset Card for WhatsThatBook

Dataset Summary

A collection of tip-of-the-tongue queries for book searches. The dataset was curated from GoodReads community forum user queries. It seves as a training and evaluation resource for tip-of-the-tongue book queries. The user queries contain the interactions on the community forum and the documents are books with associated metadata.

Supported Tasks and Leaderboards

WhatsThatBook is intended for information retrieval tasks including but not limited to standard retrieval, using just the original query posted by the user and interactive settings, where the system asks clarification queries to narrow down the user's information needs.

Languages

The dataset is primary in English, some book descriptions may contain other languages.

Dataset Structure

Data Fields

Data fields for WhatsThatBook queries:

  • question: Inital query posted to the community forum
  • question_posted_date: The date that the query was posted in YYYY-MM-DD format
  • book_id: ID of the gold book used for evaluation
  • answers: List of the gold book descriptions

The fields for the books:

  • title: The title of the book
  • author: The author of the book
  • author_url: Link to the author page
  • description The blurb of the book that contains description of the plot or
  • isbn_13: The ISBN 13 number
  • date: String representation of the date from the book webpage
  • parsed_dates:A list of the publication date parsed out in YYYY-MM-DD format
  • image_link: original link to image
  • ratings: Total number of ratings
  • reviews: Total number of reviews
  • genres: Dictionary of genre tags to number of times tagged with that genre
  • id: ID of the book, corresponding to the query file

Data Splits

The dataset is comprised of two parts, WTB (WhatsThatBook), as well as TOMT (tip-of-my-tongue). WhatsThatBook contains standard train, dev, and test splits, and TOMT serves as an evaluation set.

Dataset Creation

Source Data

Additional Information

Dataset Curators

  1. Kevin Lin, UC Berkeley, k-lin@berkeley.edu
  2. Kyle Lo, Allen Institue For Artificial Intelligence, kylel@allenai.org

Citation Information 

@article{lin2023decomposing,
  title={Decomposing Complex Queries for Tip-of-the-tongue Retrieval},
  author={Lin, Kevin and Lo, Kyle and Gonzalez, Joseph E and Klein, Dan},
  journal={arXiv preprint arXiv:2305.15053},
  year={2023}
}
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Point of Contact: k-lin@berkeley.edu
Point of Contact: k-lin@berkeley.edu