Datasets:
yonatanbitton
/
test_hf_v

Dataset card Data Studio Files Community
candidates
stringlengths
37
139
cue
stringlengths
2
14
associations
stringlengths
14
49
score_fool_the_ai
int64
0
100
num_associations
int64
2
4
num_candidates
int64
5
12
solvers_jaccard_mean
float64
0.83
1
solvers_jaccard_std
float64
0
0.24
ID
int64
0
3.56k
["rose", "food", "blanket", "folded", "noose", "hug"]
folded
["blanket", "folded"]
0
2
6
1
0
1,000
["rose", "food", "blanket", "folded", "noose", "hug"]
valentine
["rose", "hug"]
0
2
6
1
0
1,001
["stove", "home", "wheelchair", "koala", "country"]
Ride
["wheelchair", "koala"]
0
2
5
1
0
1,002
["stove", "home", "wheelchair", "koala", "country"]
location
["home", "country"]
0
2
5
1
0
1,003
["whisper", "court", "journalist", "game", "ball", "gondola"]
attention
["whisper", "court", "journalist"]
50
3
6
0.83
0.24
1,004
["whisper", "court", "journalist", "game", "ball", "gondola"]
scandalous
["whisper", "court"]
67
2
6
1
0
1,005
["whisper", "court", "journalist", "game", "ball", "gondola"]
hearing
["whisper", "court"]
0
2
6
1
0
1,006
["fall", "leaves", "product", "spiral", "month", "detergent"]
photosynthesis
["fall", "leaves"]
0
2
6
1
0
1,007
["fall", "leaves", "product", "spiral", "month", "detergent"]
veins
["fall", "leaves"]
0
2
6
1
0
1,008
["fall", "leaves", "product", "spiral", "month", "detergent"]
office
["product", "month"]
100
2
6
1
0
1,009
["fall", "leaves", "product", "spiral", "month", "detergent"]
trees
["fall", "leaves"]
0
2
6
1
0
1,010
["fall", "leaves", "product", "spiral", "month", "detergent"]
product
["product", "detergent"]
0
2
6
1
0
1,011
["food", "aunt", "sperm", "dip", "chickpea", "bridge"]
offspring
["aunt", "sperm"]
0
2
6
1
0
1,012
["food", "aunt", "sperm", "dip", "chickpea", "bridge"]
garbonzo
["food", "chickpea"]
67
2
6
1
0
1,013
["food", "aunt", "sperm", "dip", "chickpea", "bridge"]
celebration
["food", "aunt", "sperm", "dip"]
40
4
6
0.87
0.19
1,014
["food", "aunt", "sperm", "dip", "chickpea", "bridge"]
family
["aunt", "sperm"]
67
2
6
1
0
1,015
["food", "aunt", "sperm", "dip", "chickpea", "bridge"]
tomato
["food", "dip"]
67
2
6
1
0
1,016
["veranda", "hair", "compass", "man", "beard", "face"]
attractive
["man", "beard", "face"]
50
3
6
0.83
0.24
1,017
["veranda", "hair", "compass", "man", "beard", "face"]
feminine
["hair", "face"]
0
2
6
1
0
1,018
["veranda", "hair", "compass", "man", "beard", "face"]
bro
["man", "beard"]
0
2
6
1
0
1,019
["veranda", "hair", "compass", "man", "beard", "face"]
wamen
["hair", "face"]
67
2
6
1
0
1,020
["veranda", "hair", "compass", "man", "beard", "face"]
she
["hair", "face"]
67
2
6
1
0
1,021
["fruit", "sandwich", "leaping", "purple", "witch"]
flying
["leaping", "witch"]
67
2
5
1
0
1,022
["fruit", "sandwich", "leaping", "purple", "witch"]
citrus
["fruit", "sandwich"]
67
2
5
1
0
1,023
["fruit", "sandwich", "leaping", "purple", "witch"]
slice
["fruit", "sandwich"]
67
2
5
1
0
1,024
["fruit", "sandwich", "leaping", "purple", "witch"]
produce
["fruit", "sandwich", "purple"]
50
3
5
0.83
0.24
1,025
["fruit", "sandwich", "leaping", "purple", "witch"]
human
["leaping", "witch"]
67
2
5
1
0
1,026
["infection", "swine", "tomato", "apple", "yogurt", "fruit"]
acidic
["tomato", "fruit"]
0
2
6
1
0
1,027
["infection", "swine", "tomato", "apple", "yogurt", "fruit"]
cultivate
["tomato", "yogurt", "fruit"]
50
3
6
1
0
1,028
["thief", "drawing", "bank", "truck", "mask", "money"]
valuables
["thief", "bank", "money"]
50
3
6
1
0
1,029
["thief", "drawing", "bank", "truck", "mask", "money"]
move
["thief", "truck"]
67
2
6
1
0
1,030
["thief", "drawing", "bank", "truck", "mask", "money"]
disguise
["thief", "mask"]
67
2
6
1
0
1,031
["thief", "drawing", "bank", "truck", "mask", "money"]
savings
["bank", "money"]
67
2
6
1
0
1,032
["onion", "people", "chalk", "group", "knot", "eraser"]
attach
["group", "knot"]
67
2
6
1
0
1,033
["onion", "people", "chalk", "group", "knot", "eraser"]
groups
["people", "chalk", "group"]
80
3
6
1
0
1,034
["onion", "people", "chalk", "group", "knot", "eraser"]
rainbow
["chalk", "group"]
67
2
6
1
0
1,035
["onion", "people", "chalk", "group", "knot", "eraser"]
sketching
["chalk", "eraser"]
100
2
6
1
0
1,036
["tumor", "popcorn", "pictures", "digit", "camera", "creature"]
expensive
["digit", "camera"]
0
2
6
1
0
1,037
["tumor", "popcorn", "pictures", "digit", "camera", "creature"]
lighting
["pictures", "camera", "creature"]
80
3
6
1
0
1,038
["chimney", "net", "sky", "mint", "rain"]
smoke
["chimney", "sky"]
67
2
5
1
0
1,039
["chimney", "net", "sky", "mint", "rain"]
climate
["sky", "mint", "rain"]
50
3
5
1
0
1,040
["spy", "brake", "caffeine", "guy", "coffee"]
energy
["caffeine", "coffee"]
100
2
5
1
0
1,041
["spy", "brake", "caffeine", "guy", "coffee"]
caffeine
["caffeine", "coffee"]
0
2
5
1
0
1,042
["spy", "brake", "caffeine", "guy", "coffee"]
spy
["spy", "guy"]
0
2
5
1
0
1,043
["boxing", "carrot", "blood", "tile", "woman", "crucifix"]
bloody
["boxing", "blood", "crucifix"]
50
3
6
1
0
1,044
["boxing", "carrot", "blood", "tile", "woman", "crucifix"]
square
["blood", "tile"]
67
2
6
1
0
1,045
["factory", "police", "billboard", "bun", "metal", "lead"]
manufacturing
["factory", "metal"]
0
2
6
1
0
1,046
["factory", "police", "billboard", "bun", "metal", "lead"]
insurance
["factory", "police", "billboard"]
80
3
6
0.83
0.24
1,047
["factory", "police", "billboard", "bun", "metal", "lead"]
union
["factory", "police", "billboard"]
0
3
6
1
0
1,048
["horse", "salmon", "family", "car", "heart", "stallion"]
glue
["horse", "stallion"]
0
2
6
1
0
1,049
["horse", "salmon", "family", "car", "heart", "stallion"]
power
["horse", "car", "stallion"]
80
3
6
1
0
1,050
["horse", "salmon", "family", "car", "heart", "stallion"]
power
["horse", "car", "stallion"]
80
3
6
1
0
1,051
["horse", "salmon", "family", "car", "heart", "stallion"]
pump
["car", "heart"]
67
2
6
1
0
1,052
["horse", "salmon", "family", "car", "heart", "stallion"]
power
["horse", "car", "heart", "stallion"]
40
4
6
1
0
1,053
["lad", "fight", "karate", "foil", "swamp"]
Competitive
["fight", "karate"]
67
2
5
1
0
1,054
["lad", "fight", "karate", "foil", "swamp"]
win
["fight", "karate"]
67
2
5
1
0
1,055
["lad", "fight", "karate", "foil", "swamp"]
reflect
["foil", "swamp"]
67
2
5
1
0
1,056
["lad", "fight", "karate", "foil", "swamp"]
combat
["fight", "karate"]
0
2
5
1
0
1,057
["wrestler", "suds", "bread", "field", "grain", "hot dog"]
sprouting
["field", "grain"]
0
2
6
1
0
1,058
["wrestler", "suds", "bread", "field", "grain", "hot dog"]
feed
["bread", "grain", "hot dog"]
50
3
6
1
0
1,059
["wrestler", "suds", "bread", "field", "grain", "hot dog"]
trio
["wrestler", "hot dog"]
67
2
6
1
0
1,060
["blood", "woman", "silky", "lottery", "wool"]
long
["woman", "silky", "wool"]
0
3
5
0.83
0.24
1,061
["blood", "woman", "silky", "lottery", "wool"]
risky
["blood", "lottery"]
67
2
5
1
0
1,062
["blood", "woman", "silky", "lottery", "wool"]
staring
["woman", "silky"]
0
2
5
1
0
1,063
["blood", "woman", "silky", "lottery", "wool"]
brush
["woman", "silky"]
0
2
5
1
0
1,064
["blood", "woman", "silky", "lottery", "wool"]
golddigger
["woman", "lottery"]
0
2
5
1
0
1,065
["meat", "catch", "red", "dagger", "mug", "cow"]
freerange
["meat", "cow"]
0
2
6
1
0
1,066
["meat", "catch", "red", "dagger", "mug", "cow"]
cut
["meat", "dagger"]
67
2
6
1
0
1,067
["meat", "catch", "red", "dagger", "mug", "cow"]
head
["catch", "cow"]
67
2
6
1
0
1,068
["meat", "catch", "red", "dagger", "mug", "cow"]
slaughter
["meat", "dagger", "cow"]
0
3
6
1
0
1,069
["meat", "catch", "red", "dagger", "mug", "cow"]
meat
["meat", "red", "cow"]
50
3
6
1
0
1,070
["icing", "nail polish", "truck", "fox", "artist", "carry"]
practice
["artist", "carry"]
67
2
6
1
0
1,071
["icing", "nail polish", "truck", "fox", "artist", "carry"]
fast
["truck", "fox"]
67
2
6
1
0
1,072
["icing", "nail polish", "truck", "fox", "artist", "carry"]
stroke
["nail polish", "artist"]
100
2
6
1
0
1,073
["icing", "nail polish", "truck", "fox", "artist", "carry"]
mass
["truck", "carry"]
67
2
6
1
0
1,074
["icing", "nail polish", "truck", "fox", "artist", "carry"]
swirly
["icing", "artist"]
67
2
6
1
0
1,075
["shorts", "foam", "starch", "shadow", "smoke", "cigar"]
toxin
["smoke", "cigar"]
100
2
6
1
0
1,076
["shorts", "foam", "starch", "shadow", "smoke", "cigar"]
relax
["shorts", "foam", "smoke", "cigar"]
40
4
6
1
0
1,077
["shorts", "foam", "starch", "shadow", "smoke", "cigar"]
cancer
["smoke", "cigar"]
100
2
6
1
0
1,078
["shorts", "foam", "starch", "shadow", "smoke", "cigar"]
consumable
["starch", "smoke", "cigar"]
50
3
6
1
0
1,079
["list", "lotion", "library", "drink", "book", "magazine"]
hydration
["lotion", "drink"]
67
2
6
1
0
1,080
["list", "lotion", "library", "drink", "book", "magazine"]
moisture
["lotion", "drink"]
67
2
6
1
0
1,081
["rock", "liquid", "sesame", "earring", "laugh", "sheriff"]
moist
["liquid", "laugh"]
0
2
6
1
0
1,082
["rock", "liquid", "sesame", "earring", "laugh", "sheriff"]
Numerous
["sesame", "earring", "sheriff"]
100
3
6
1
0
1,083
["rock", "liquid", "sesame", "earring", "laugh", "sheriff"]
Emotional
["laugh", "sheriff"]
67
2
6
1
0
1,084
["rock", "liquid", "sesame", "earring", "laugh", "sheriff"]
drop
["liquid", "laugh"]
0
2
6
1
0
1,085
["red", "watch", "tea", "blush", "eucalyptus", "hockey"]
drop
["tea", "eucalyptus", "hockey"]
80
3
6
0.83
0.24
1,086
["red", "watch", "tea", "blush", "eucalyptus", "hockey"]
teabag
["tea", "eucalyptus"]
0
2
6
1
0
1,087
["red", "watch", "tea", "blush", "eucalyptus", "hockey"]
injury
["red", "hockey"]
67
2
6
1
0
1,088
["red", "watch", "tea", "blush", "eucalyptus", "hockey"]
blush
["red", "blush"]
67
2
6
1
0
1,089
["goose", "oil", "compass", "liquid", "water", "milk"]
standing
["goose", "oil", "milk"]
50
3
6
1
0
1,090
["goose", "oil", "compass", "liquid", "water", "milk"]
migrate
["goose", "compass"]
67
2
6
1
0
1,091
["goose", "oil", "compass", "liquid", "water", "milk"]
migrate
["goose", "compass"]
67
2
6
1
0
1,092
["check", "snow", "freezing", "hot", "marsh"]
shiver
["snow", "freezing"]
0
2
5
1
0
1,093
["check", "snow", "freezing", "hot", "marsh"]
extremes
["snow", "hot"]
67
2
5
1
0
1,094
["check", "snow", "freezing", "hot", "marsh"]
opposite
["snow", "hot"]
67
2
5
1
0
1,095
["check", "snow", "freezing", "hot", "marsh"]
informative
["check", "hot"]
67
2
5
1
0
1,096
["mud", "dust", "doodle", "beak", "earth"]
trees
["beak", "earth"]
100
2
5
1
0
1,097
["mud", "dust", "doodle", "beak", "earth"]
forest
["beak", "earth"]
100
2
5
1
0
1,098
["mud", "dust", "doodle", "beak", "earth"]
vast
["dust", "earth"]
0
2
5
1
0
1,099