id stringclasses 6 values	X stringclasses 6 values	Y stringclasses 5 values	A stringclasses 3 values	B stringclasses 3 values
europeanamerican_africanamerican_pleasant_unpleasant	european_american_names	african_american_names	pleasant	unpleasant
flowers_insects_pleasant_unpleasant	flowers	insects	pleasant	unpleasant
male_female_career_family	male_names	female_names	career_words	family_words
math_arts_male_female	math_words	arts_words	male_attributes	female_attributes
musicalinstruments_weapons_pleasant_unpleasant	musical_instruments	weapons	pleasant	unpleasant
science_arts_male_female	science_words	arts_words	male_attributes	female_attributes

Usage

When downloading, specify which files you want to download and set the split to train (required by datasets).

from datasets import load_dataset

words = load_dataset("fairnlp/weat", data_files=["words.parquet"], split="train")
associations = load_dataset("fairnlp/weat", data_files=["associations_weat.parquet"], split="train")

Dataset Card for Word Embedding Association Test (WEAT)

This dataset contains the source words of the original Word Embedding Association Test (WEAT) as described by Caliskan et. al. (2016).

Dataset Details

The dataset contains word lists and attribute lists used to compute several WEAT scores for different embedding associations. For details on the methodology, please refer to the original paper. This dataset is contributed to Hugging Face as part of the WEAT implementation in the FairNLP fairscore library.

Dataset Sources

Paper [optional]: lcs.bath.ac.uk/~jjb/ftp/CaliskanSemantics-Arxiv.pdf

BibTeX:

@article{DBLP:journals/corr/IslamBN16,
  author       = {Aylin Caliskan Islam and
                  Joanna J. Bryson and
                  Arvind Narayanan},
  title        = {Semantics derived automatically from language corpora necessarily
                  contain human biases},
  journal      = {CoRR},
  volume       = {abs/1608.07187},
  year         = {2016},
  url          = {http://arxiv.org/abs/1608.07187},
  eprinttype    = {arXiv},
  eprint       = {1608.07187},
  timestamp    = {Sat, 23 Jan 2021 01:20:12 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/IslamBN16.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}