word
stringlengths
3
19
pos
stringclasses
9 values
slavishness
NOUN
abhorring
NOUN
passivism
NOUN
discomfits
NOUN
consequentialist
NOUN
judgmentalism
NOUN
niebuhrian
PROPN
ressentiment
NOUN
constitutionalize
VERB
exclusionist
NOUN
cravenness
ADJ
postmodernists
VERB
arrogation
NOUN
caviling
VERB
essentialist
NOUN
heterodoxy
PROPN
absolutist
NOUN
irreconcilability
NOUN
unilateralism
NOUN
exceptionalists
NOUN
charlatanry
NOUN
intransigently
ADV
reactionary
ADJ
exceptionalist
NOUN
instrumentalization
NOUN
burkean
PROPN
delegitimation
NOUN
quietism
NOUN
misandry
VERB
vulgarisation
NOUN
declinism
NOUN
particularist
NOUN
establishmentarian
ADJ
contemptuous
ADJ
monarchism
NOUN
temporize
VERB
bureaucratisation
NOUN
pusillanimity
NOUN
presumptuousness
NOUN
deracination
VERB
russophobic
ADJ
sneered
VERB
mad
ADJ
exasperated
VERB
sympathic
ADJ
exclaim
VERB
maddens
NOUN
incredulous
ADJ
disconcerts
NOUN
discomfit
VERB
schoolmarmish
VERB
disdainful
ADJ
insolent
NOUN
amused
VERB
angry
ADJ
indignant
NOUN
cringe
VERB
unnerving
VERB
annoyed
VERB
blunt
NOUN
thickheaded
VERB
riled
VERB
sneering
VERB
bemuses
NOUN
smirking
VERB
gleeful
ADJ
scold
VERB
taunt
NOUN
infuriating
VERB
nonplused
VERB
overcritical
PROPN
bewilders
NOUN
brusk
PROPN
dismissive
ADJ
appals
NOUN
baffling
VERB
blabbered
VERB
mocking
VERB
overthinks
VERB
peeving
VERB
obnoxious
ADJ
flummoxes
NOUN
hysterical
ADJ
blasé
PROPN
unhinged
VERB
wince
PROPN
ascerbic
VERB
pshaw
NOUN
grumbly
ADV
snickered
VERB
intellectualise
VERB
traumatises
VERB
sarcastic
ADJ
gabbled
VERB
unspontaneous
ADJ
paranoid
ADJ
hurted
VERB
disconcert
NOUN
chortled
VERB
nakedly
ADV
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Description:

The bias_lexicon file is a comprehensive dictionary of biased words. This lexicon is designed to assist in identifying and analyzing biased language in various texts. The dictionary encompasses a wide range of words that are often associated with biased expressions, including those related to gender, race, age, and other social categories.

Usage:

This resource can be pivotal for crafting features in natural language processing (NLP) tasks, sentiment analysis, and in developing models that aim to detect or mitigate biased language. It's particularly useful in research and applications focusing on ethical AI and fair representation in language models.

Downloads last month
27
Edit dataset card