research-backup/relbert-roberta-base-semeval2012-v6-average-prompt-a-loob-0
Feature Extraction • Updated
• 12
level stringclasses 3 values | relation_type stringlengths 1 3 | positives sequence | negatives sequence |
|---|---|---|---|
parent | 6 | [
[
"prisoner",
"freedom"
],
[
"watch",
"blindly"
],
[
"old",
"youth"
],
[
"fill",
"empty"
],
[
"deceased",
"alive"
],
[
"speed",
"slowly"
],
[
"empty",
"full"
],
[
"miser",
"splurge"
],
[
"integrity",
"dishonest"
... | [
[
"touch",
"grope"
],
[
"home",
"kitchen"
],
[
"factory",
"car"
],
[
"snake",
"legs"
],
[
"sign",
"direction"
],
[
"doctor",
"degree"
],
[
"musician",
"instrument"
],
[
"persuade",
"force"
],
[
"arsenal",
"weapon... |
parent | 8 | [
[
"exercise",
"fitness"
],
[
"antibiotic",
"infection"
],
[
"thirsty",
"drink"
],
[
"gas",
"furnace"
],
[
"bath",
"cleanliness"
],
[
"students",
"graduation"
],
[
"exercise",
"fitness"
],
[
"accident",
"damage"
],
[
... | [
[
"body",
"flesh"
],
[
"blemish",
"skin"
],
[
"below",
"above"
],
[
"acclaim",
"disgrace"
],
[
"game",
"referee"
],
[
"crown",
"royalty"
],
[
"office",
"computer"
],
[
"operate",
"machine"
],
[
"sharpen",
"dull"
... |
parent | 7 | [
[
"prescription",
"patient"
],
[
"coach",
"player"
],
[
"physician",
"degree"
],
[
"paper",
"pen"
],
[
"play",
"instrument"
],
[
"treatment",
"patient"
],
[
"therapist",
"client"
],
[
"coach",
"athlete"
],
[
"owner",... | [
[
"building",
"lobby"
],
[
"rotten",
"stink"
],
[
"repair",
"damaged"
],
[
"work",
"earn"
],
[
"dynamite",
"explode"
],
[
"hand",
"finger"
],
[
"clothing",
"shirt"
],
[
"breathing",
"hyperventilating"
],
[
"fast",
... |
parent | 5 | [
[
"saint",
"holiness"
],
[
"wash",
"clean"
],
[
"tired",
"exhaustion"
],
[
"fill",
"empty"
],
[
"fish",
"swim"
],
[
"dead",
"rot"
],
[
"snow",
"cold"
],
[
"tycoon",
"wealthy"
],
[
"crying",
"sad"
],
[
"co... | [
[
"germs",
"sickness"
],
[
"lie",
"honestly"
],
[
"book",
"magazine"
],
[
"above",
"below"
],
[
"barber",
"scissors"
],
[
"gardener",
"shovel"
],
[
"preacher",
"parishioner"
],
[
"bank",
"river"
],
[
"breathe",
"... |
parent | 4 | [
[
"cooked",
"raw"
],
[
"young",
"old"
],
[
"start",
"finish"
],
[
"smooth",
"rough"
],
[
"freezing",
"warm"
],
[
"low",
"up"
],
[
"day",
"evening"
],
[
"alive",
"dead"
],
[
"crack",
"glass"
],
[
"blemish"... | [
[
"snacks",
"chips"
],
[
"coward",
"fear"
],
[
"heat",
"hot"
],
[
"invincible",
"defeated"
],
[
"morning",
"sunrise"
],
[
"thirst",
"drink"
],
[
"makeup",
"blemishes"
],
[
"game",
"referee"
],
[
"garden",
"flower... |
parent | 3 | [
[
"tired",
"exhausted"
],
[
"jog",
"run"
],
[
"puppy",
"dog"
],
[
"sword",
"knife"
],
[
"cute",
"adorable"
],
[
"man",
"woman"
],
[
"pencil",
"pen"
],
[
"flood",
"water"
],
[
"dim",
"light"
],
[
"discipli... | [
[
"script",
"movie"
],
[
"carpet",
"fibers"
],
[
"driver",
"license"
],
[
"artist",
"art"
],
[
"malleable",
"bend"
],
[
"award",
"winner"
],
[
"play",
"instrument"
],
[
"progress",
"regress"
],
[
"pitching",
"bas... |
parent | 1 | [
[
"smoke",
"fire"
],
[
"coins",
"pennies"
],
[
"sunglasses",
"eyes"
],
[
"flower",
"daisy"
],
[
"groan",
"pain"
],
[
"weapon",
"spear"
],
[
"map",
"route"
],
[
"meteorology",
"weather"
],
[
"tears",
"sorrow"
],... | [
[
"wash",
"clean"
],
[
"loss",
"grief"
],
[
"hot",
"cold"
],
[
"birth",
"death"
],
[
"eat",
"delicious"
],
[
"exercise",
"healthy"
],
[
"glue",
"adhesion"
],
[
"hospital",
"patient"
],
[
"seed",
"plant"
],
[
... |
parent | 10 | [
[
"kiss",
"love"
],
[
"landscape",
"photo"
],
[
"smile",
"happiness"
],
[
"choreography",
"performance"
],
[
"meteorology",
"weather"
],
[
"tear",
"sadness"
],
[
"pregnancy",
"baby"
],
[
"king",
"crown"
],
[
"license... | [
[
"big",
"small"
],
[
"glue",
"sticky"
],
[
"bigot",
"hateful"
],
[
"library",
"books"
],
[
"start",
"finish"
],
[
"kind",
"cruelty"
],
[
"ocean",
"water"
],
[
"drunk",
"intoxication"
],
[
"teach",
"educated"
]... |
parent | 9 | [
[
"morning",
"sunrise"
],
[
"laboratory",
"experimenting"
],
[
"margin",
"paper"
],
[
"winter",
"christmas"
],
[
"puberty",
"hormones"
],
[
"stream",
"bank"
],
[
"foreword",
"novel"
],
[
"office",
"desk"
],
[
"title"... | [
[
"kiss",
"love"
],
[
"loss",
"grief"
],
[
"award",
"winner"
],
[
"gigantic",
"short"
],
[
"fish",
"swim"
],
[
"difficult",
"easy"
],
[
"danger",
"flee"
],
[
"good",
"wrong"
],
[
"fail",
"succeed"
],
[
"n... |
parent | 2 | [
[
"arsenal",
"weapons"
],
[
"circus",
"ringmaster"
],
[
"cave",
"entrance"
],
[
"corpse",
"breath"
],
[
"body",
"flesh"
],
[
"ocean",
"dryness"
],
[
"chewing",
"eating"
],
[
"desk",
"wood"
],
[
"woman",
"penis"
... | [
[
"snow",
"cold"
],
[
"go",
"stay"
],
[
"bakery",
"cake"
],
[
"trim",
"shorten"
],
[
"hunter",
"rifle"
],
[
"carpet",
"vacuum"
],
[
"malleable",
"bend"
],
[
"conception",
"birth"
],
[
"smoke",
"fire"
],
[
... |
child | 4a | [
[
"happy",
"sad"
],
[
"full",
"empty"
],
[
"dry",
"wet"
],
[
"rich",
"poor"
],
[
"young",
"old"
],
[
"smooth",
"rough"
],
[
"noise",
"silence"
],
[
"cooked",
"raw"
]
] | [
[
"shine",
"dimly"
],
[
"run",
"exercise"
],
[
"majority",
"small"
],
[
"shoe",
"foot"
],
[
"butcher",
"knife"
],
[
"lubricant",
"oil"
],
[
"pain",
"medicate"
],
[
"rest",
"restorative"
],
[
"dismayed",
"depresse... |
child | 5e | [
[
"tailor",
"sew"
],
[
"pastor",
"preach"
],
[
"dog",
"bark"
],
[
"chef",
"cook"
],
[
"heart",
"beat"
],
[
"lion",
"roar"
],
[
"dynamite",
"explode"
],
[
"fish",
"swim"
]
] | [
[
"young",
"old"
],
[
"baby",
"adult"
],
[
"recipe",
"ingredient"
],
[
"utensils",
"forks"
],
[
"hunter",
"rifle"
],
[
"boat",
"ship"
],
[
"athlete",
"fit"
],
[
"antibiotics",
"bacteria"
],
[
"wound",
"bandage"
... |
IMPORTANT: This is the same dataset as relbert/semeval2012_relational_similarity, but with a different dataset construction.
Relational similarity dataset from SemEval2012 task 2, compiled to fine-tune RelBERT model. The dataset contains a list of positive and negative word pair from 89 pre-defined relations. The relation types are constructed on top of following 10 parent relation types.
{
1: "Class Inclusion", # Hypernym
2: "Part-Whole", # Meronym, Substance Meronym
3: "Similar", # Synonym, Co-hypornym
4: "Contrast", # Antonym
5: "Attribute", # Attribute, Event
6: "Non Attribute",
7: "Case Relation",
8: "Cause-Purpose",
9: "Space-Time",
10: "Representation"
}
Each of the parent relation is further grouped into child relation types where the definition can be found here.
An example of train looks as follows.
{
'relation_type': '8d',
'positives': [ [ "breathe", "live" ], [ "study", "learn" ], [ "speak", "communicate" ], ... ]
'negatives': [ [ "starving", "hungry" ], [ "clean", "bathe" ], [ "hungry", "starving" ], ... ]
}
| name | train | validation |
|---|---|---|
| semeval2012_relational_similarity | 89 | 89 |
| positives | negatives | |
|---|---|---|
| ('1', 'parent', 'train') | 88 | 544 |
| ('1', 'parent', 'validation') | 22 | 136 |
| ('10', 'parent', 'train') | 48 | 584 |
| ('10', 'parent', 'validation') | 12 | 146 |
| ('10a', 'child', 'train') | 8 | 1324 |
| ('10a', 'child', 'validation') | 2 | 331 |
| ('10a', 'child_prototypical', 'train') | 194 | 1917 |
| ('10a', 'child_prototypical', 'validation') | 52 | 521 |
| ('10b', 'child', 'train') | 8 | 1325 |
| ('10b', 'child', 'validation') | 2 | 331 |
| ('10b', 'child_prototypical', 'train') | 180 | 1558 |
| ('10b', 'child_prototypical', 'validation') | 54 | 469 |
| ('10c', 'child', 'train') | 8 | 1327 |
| ('10c', 'child', 'validation') | 2 | 331 |
| ('10c', 'child_prototypical', 'train') | 170 | 1640 |
| ('10c', 'child_prototypical', 'validation') | 40 | 390 |
| ('10d', 'child', 'train') | 8 | 1328 |
| ('10d', 'child', 'validation') | 2 | 331 |
| ('10d', 'child_prototypical', 'train') | 154 | 1390 |
| ('10d', 'child_prototypical', 'validation') | 44 | 376 |
| ('10e', 'child', 'train') | 8 | 1329 |
| ('10e', 'child', 'validation') | 2 | 332 |
| ('10e', 'child_prototypical', 'train') | 134 | 884 |
| ('10e', 'child_prototypical', 'validation') | 40 | 234 |
| ('10f', 'child', 'train') | 8 | 1328 |
| ('10f', 'child', 'validation') | 2 | 331 |
| ('10f', 'child_prototypical', 'train') | 160 | 1460 |
| ('10f', 'child_prototypical', 'validation') | 38 | 306 |
| ('1a', 'child', 'train') | 8 | 1324 |
| ('1a', 'child', 'validation') | 2 | 331 |
| ('1a', 'child_prototypical', 'train') | 212 | 1854 |
| ('1a', 'child_prototypical', 'validation') | 34 | 338 |
| ('1b', 'child', 'train') | 8 | 1324 |
| ('1b', 'child', 'validation') | 2 | 331 |
| ('1b', 'child_prototypical', 'train') | 190 | 1712 |
| ('1b', 'child_prototypical', 'validation') | 56 | 480 |
| ('1c', 'child', 'train') | 8 | 1327 |
| ('1c', 'child', 'validation') | 2 | 331 |
| ('1c', 'child_prototypical', 'train') | 160 | 1528 |
| ('1c', 'child_prototypical', 'validation') | 50 | 502 |
| ('1d', 'child', 'train') | 8 | 1323 |
| ('1d', 'child', 'validation') | 2 | 330 |
| ('1d', 'child_prototypical', 'train') | 224 | 2082 |
| ('1d', 'child_prototypical', 'validation') | 46 | 458 |
| ('1e', 'child', 'train') | 8 | 1329 |
| ('1e', 'child', 'validation') | 2 | 332 |
| ('1e', 'child_prototypical', 'train') | 126 | 775 |
| ('1e', 'child_prototypical', 'validation') | 48 | 256 |
| ('2', 'parent', 'train') | 80 | 552 |
| ('2', 'parent', 'validation') | 20 | 138 |
| ('2a', 'child', 'train') | 8 | 1324 |
| ('2a', 'child', 'validation') | 2 | 330 |
| ('2a', 'child_prototypical', 'train') | 186 | 1885 |
| ('2a', 'child_prototypical', 'validation') | 72 | 736 |
| ('2b', 'child', 'train') | 8 | 1327 |
| ('2b', 'child', 'validation') | 2 | 331 |
| ('2b', 'child_prototypical', 'train') | 172 | 1326 |
| ('2b', 'child_prototypical', 'validation') | 38 | 284 |
| ('2c', 'child', 'train') | 8 | 1325 |
| ('2c', 'child', 'validation') | 2 | 331 |
| ('2c', 'child_prototypical', 'train') | 192 | 1773 |
| ('2c', 'child_prototypical', 'validation') | 42 | 371 |
| ('2d', 'child', 'train') | 8 | 1328 |
| ('2d', 'child', 'validation') | 2 | 331 |
| ('2d', 'child_prototypical', 'train') | 158 | 1329 |
| ('2d', 'child_prototypical', 'validation') | 40 | 338 |
| ('2e', 'child', 'train') | 8 | 1327 |
| ('2e', 'child', 'validation') | 2 | 331 |
| ('2e', 'child_prototypical', 'train') | 164 | 1462 |
| ('2e', 'child_prototypical', 'validation') | 46 | 463 |
| ('2f', 'child', 'train') | 8 | 1327 |
| ('2f', 'child', 'validation') | 2 | 331 |
| ('2f', 'child_prototypical', 'train') | 176 | 1869 |
| ('2f', 'child_prototypical', 'validation') | 34 | 371 |
| ('2g', 'child', 'train') | 8 | 1323 |
| ('2g', 'child', 'validation') | 2 | 330 |
| ('2g', 'child_prototypical', 'train') | 216 | 1925 |
| ('2g', 'child_prototypical', 'validation') | 54 | 480 |
| ('2h', 'child', 'train') | 8 | 1327 |
| ('2h', 'child', 'validation') | 2 | 331 |
| ('2h', 'child_prototypical', 'train') | 168 | 1540 |
| ('2h', 'child_prototypical', 'validation') | 42 | 385 |
| ('2i', 'child', 'train') | 8 | 1328 |
| ('2i', 'child', 'validation') | 2 | 332 |
| ('2i', 'child_prototypical', 'train') | 144 | 1335 |
| ('2i', 'child_prototypical', 'validation') | 42 | 371 |
| ('2j', 'child', 'train') | 8 | 1328 |
| ('2j', 'child', 'validation') | 2 | 331 |
| ('2j', 'child_prototypical', 'train') | 160 | 1595 |
| ('2j', 'child_prototypical', 'validation') | 38 | 369 |
| ('3', 'parent', 'train') | 64 | 568 |
| ('3', 'parent', 'validation') | 16 | 142 |
| ('3a', 'child', 'train') | 8 | 1327 |
| ('3a', 'child', 'validation') | 2 | 331 |
| ('3a', 'child_prototypical', 'train') | 174 | 1597 |
| ('3a', 'child_prototypical', 'validation') | 36 | 328 |
| ('3b', 'child', 'train') | 8 | 1327 |
| ('3b', 'child', 'validation') | 2 | 331 |
| ('3b', 'child_prototypical', 'train') | 174 | 1833 |
| ('3b', 'child_prototypical', 'validation') | 36 | 407 |
| ('3c', 'child', 'train') | 8 | 1326 |
| ('3c', 'child', 'validation') | 2 | 331 |
| ('3c', 'child_prototypical', 'train') | 186 | 1664 |
| ('3c', 'child_prototypical', 'validation') | 36 | 315 |
| ('3d', 'child', 'train') | 8 | 1324 |
| ('3d', 'child', 'validation') | 2 | 331 |
| ('3d', 'child_prototypical', 'train') | 202 | 1943 |
| ('3d', 'child_prototypical', 'validation') | 44 | 372 |
| ('3e', 'child', 'train') | 8 | 1332 |
| ('3e', 'child', 'validation') | 2 | 332 |
| ('3e', 'child_prototypical', 'train') | 98 | 900 |
| ('3e', 'child_prototypical', 'validation') | 40 | 368 |
| ('3f', 'child', 'train') | 8 | 1327 |
| ('3f', 'child', 'validation') | 2 | 331 |
| ('3f', 'child_prototypical', 'train') | 180 | 1983 |
| ('3f', 'child_prototypical', 'validation') | 30 | 362 |
| ('3g', 'child', 'train') | 8 | 1331 |
| ('3g', 'child', 'validation') | 2 | 332 |
| ('3g', 'child_prototypical', 'train') | 122 | 1089 |
| ('3g', 'child_prototypical', 'validation') | 28 | 251 |
| ('3h', 'child', 'train') | 8 | 1328 |
| ('3h', 'child', 'validation') | 2 | 331 |
| ('3h', 'child_prototypical', 'train') | 142 | 1399 |
| ('3h', 'child_prototypical', 'validation') | 56 | 565 |
| ('4', 'parent', 'train') | 64 | 568 |
| ('4', 'parent', 'validation') | 16 | 142 |
| ('4a', 'child', 'train') | 8 | 1327 |
| ('4a', 'child', 'validation') | 2 | 331 |
| ('4a', 'child_prototypical', 'train') | 170 | 1766 |
| ('4a', 'child_prototypical', 'validation') | 40 | 474 |
| ('4b', 'child', 'train') | 8 | 1330 |
| ('4b', 'child', 'validation') | 2 | 332 |
| ('4b', 'child_prototypical', 'train') | 132 | 949 |
| ('4b', 'child_prototypical', 'validation') | 30 | 214 |
| ('4c', 'child', 'train') | 8 | 1326 |
| ('4c', 'child', 'validation') | 2 | 331 |
| ('4c', 'child_prototypical', 'train') | 172 | 1755 |
| ('4c', 'child_prototypical', 'validation') | 50 | 446 |
| ('4d', 'child', 'train') | 8 | 1332 |
| ('4d', 'child', 'validation') | 2 | 333 |
| ('4d', 'child_prototypical', 'train') | 92 | 531 |
| ('4d', 'child_prototypical', 'validation') | 34 | 218 |
| ('4e', 'child', 'train') | 8 | 1326 |
| ('4e', 'child', 'validation') | 2 | 331 |
| ('4e', 'child_prototypical', 'train') | 184 | 2021 |
| ('4e', 'child_prototypical', 'validation') | 38 | 402 |
| ('4f', 'child', 'train') | 8 | 1328 |
| ('4f', 'child', 'validation') | 2 | 332 |
| ('4f', 'child_prototypical', 'train') | 144 | 1464 |
| ('4f', 'child_prototypical', 'validation') | 42 | 428 |
| ('4g', 'child', 'train') | 8 | 1324 |
| ('4g', 'child', 'validation') | 2 | 330 |
| ('4g', 'child_prototypical', 'train') | 212 | 2057 |
| ('4g', 'child_prototypical', 'validation') | 46 | 435 |
| ('4h', 'child', 'train') | 8 | 1326 |
| ('4h', 'child', 'validation') | 2 | 331 |
| ('4h', 'child_prototypical', 'train') | 170 | 1787 |
| ('4h', 'child_prototypical', 'validation') | 52 | 525 |
| ('5', 'parent', 'train') | 72 | 560 |
| ('5', 'parent', 'validation') | 18 | 140 |
| ('5a', 'child', 'train') | 8 | 1324 |
| ('5a', 'child', 'validation') | 2 | 331 |
| ('5a', 'child_prototypical', 'train') | 202 | 1876 |
| ('5a', 'child_prototypical', 'validation') | 44 | 439 |
| ('5b', 'child', 'train') | 8 | 1329 |
| ('5b', 'child', 'validation') | 2 | 332 |
| ('5b', 'child_prototypical', 'train') | 140 | 1310 |
| ('5b', 'child_prototypical', 'validation') | 34 | 330 |
| ('5c', 'child', 'train') | 8 | 1327 |
| ('5c', 'child', 'validation') | 2 | 331 |
| ('5c', 'child_prototypical', 'train') | 170 | 1552 |
| ('5c', 'child_prototypical', 'validation') | 40 | 373 |
| ('5d', 'child', 'train') | 8 | 1324 |
| ('5d', 'child', 'validation') | 2 | 330 |
| ('5d', 'child_prototypical', 'train') | 204 | 1783 |
| ('5d', 'child_prototypical', 'validation') | 54 | 580 |
| ('5e', 'child', 'train') | 8 | 1329 |
| ('5e', 'child', 'validation') | 2 | 332 |
| ('5e', 'child_prototypical', 'train') | 136 | 1283 |
| ('5e', 'child_prototypical', 'validation') | 38 | 357 |
| ('5f', 'child', 'train') | 8 | 1327 |
| ('5f', 'child', 'validation') | 2 | 331 |
| ('5f', 'child_prototypical', 'train') | 154 | 1568 |
| ('5f', 'child_prototypical', 'validation') | 56 | 567 |
| ('5g', 'child', 'train') | 8 | 1328 |
| ('5g', 'child', 'validation') | 2 | 332 |
| ('5g', 'child_prototypical', 'train') | 158 | 1626 |
| ('5g', 'child_prototypical', 'validation') | 28 | 266 |
| ('5h', 'child', 'train') | 8 | 1324 |
| ('5h', 'child', 'validation') | 2 | 330 |
| ('5h', 'child_prototypical', 'train') | 218 | 2348 |
| ('5h', 'child_prototypical', 'validation') | 40 | 402 |
| ('5i', 'child', 'train') | 8 | 1324 |
| ('5i', 'child', 'validation') | 2 | 331 |
| ('5i', 'child_prototypical', 'train') | 192 | 2010 |
| ('5i', 'child_prototypical', 'validation') | 54 | 551 |
| ('6', 'parent', 'train') | 64 | 568 |
| ('6', 'parent', 'validation') | 16 | 142 |
| ('6a', 'child', 'train') | 8 | 1324 |
| ('6a', 'child', 'validation') | 2 | 330 |
| ('6a', 'child_prototypical', 'train') | 204 | 1962 |
| ('6a', 'child_prototypical', 'validation') | 54 | 530 |
| ('6b', 'child', 'train') | 8 | 1327 |
| ('6b', 'child', 'validation') | 2 | 331 |
| ('6b', 'child_prototypical', 'train') | 180 | 1840 |
| ('6b', 'child_prototypical', 'validation') | 30 | 295 |
| ('6c', 'child', 'train') | 8 | 1325 |
| ('6c', 'child', 'validation') | 2 | 331 |
| ('6c', 'child_prototypical', 'train') | 180 | 1968 |
| ('6c', 'child_prototypical', 'validation') | 54 | 527 |
| ('6d', 'child', 'train') | 8 | 1328 |
| ('6d', 'child', 'validation') | 2 | 331 |
| ('6d', 'child_prototypical', 'train') | 164 | 1903 |
| ('6d', 'child_prototypical', 'validation') | 34 | 358 |
| ('6e', 'child', 'train') | 8 | 1327 |
| ('6e', 'child', 'validation') | 2 | 331 |
| ('6e', 'child_prototypical', 'train') | 170 | 1737 |
| ('6e', 'child_prototypical', 'validation') | 40 | 398 |
| ('6f', 'child', 'train') | 8 | 1326 |
| ('6f', 'child', 'validation') | 2 | 331 |
| ('6f', 'child_prototypical', 'train') | 174 | 1652 |
| ('6f', 'child_prototypical', 'validation') | 48 | 438 |
| ('6g', 'child', 'train') | 8 | 1326 |
| ('6g', 'child', 'validation') | 2 | 331 |
| ('6g', 'child_prototypical', 'train') | 188 | 1740 |
| ('6g', 'child_prototypical', 'validation') | 34 | 239 |
| ('6h', 'child', 'train') | 8 | 1324 |
| ('6h', 'child', 'validation') | 2 | 330 |
| ('6h', 'child_prototypical', 'train') | 230 | 2337 |
| ('6h', 'child_prototypical', 'validation') | 28 | 284 |
| ('7', 'parent', 'train') | 64 | 568 |
| ('7', 'parent', 'validation') | 16 | 142 |
| ('7a', 'child', 'train') | 8 | 1324 |
| ('7a', 'child', 'validation') | 2 | 331 |
| ('7a', 'child_prototypical', 'train') | 198 | 2045 |
| ('7a', 'child_prototypical', 'validation') | 48 | 516 |
| ('7b', 'child', 'train') | 8 | 1330 |
| ('7b', 'child', 'validation') | 2 | 332 |
| ('7b', 'child_prototypical', 'train') | 138 | 905 |
| ('7b', 'child_prototypical', 'validation') | 24 | 177 |
| ('7c', 'child', 'train') | 8 | 1327 |
| ('7c', 'child', 'validation') | 2 | 331 |
| ('7c', 'child_prototypical', 'train') | 170 | 1402 |
| ('7c', 'child_prototypical', 'validation') | 40 | 313 |
| ('7d', 'child', 'train') | 8 | 1324 |
| ('7d', 'child', 'validation') | 2 | 331 |
| ('7d', 'child_prototypical', 'train') | 196 | 2064 |
| ('7d', 'child_prototypical', 'validation') | 50 | 497 |
| ('7e', 'child', 'train') | 8 | 1328 |
| ('7e', 'child', 'validation') | 2 | 331 |
| ('7e', 'child_prototypical', 'train') | 156 | 1270 |
| ('7e', 'child_prototypical', 'validation') | 42 | 298 |
| ('7f', 'child', 'train') | 8 | 1326 |
| ('7f', 'child', 'validation') | 2 | 331 |
| ('7f', 'child_prototypical', 'train') | 178 | 1377 |
| ('7f', 'child_prototypical', 'validation') | 44 | 380 |
| ('7g', 'child', 'train') | 8 | 1328 |
| ('7g', 'child', 'validation') | 2 | 332 |
| ('7g', 'child_prototypical', 'train') | 144 | 885 |
| ('7g', 'child_prototypical', 'validation') | 42 | 263 |
| ('7h', 'child', 'train') | 8 | 1324 |
| ('7h', 'child', 'validation') | 2 | 331 |
| ('7h', 'child_prototypical', 'train') | 188 | 1479 |
| ('7h', 'child_prototypical', 'validation') | 58 | 467 |
| ('8', 'parent', 'train') | 64 | 568 |
| ('8', 'parent', 'validation') | 16 | 142 |
| ('8a', 'child', 'train') | 8 | 1324 |
| ('8a', 'child', 'validation') | 2 | 331 |
| ('8a', 'child_prototypical', 'train') | 186 | 1640 |
| ('8a', 'child_prototypical', 'validation') | 60 | 552 |
| ('8b', 'child', 'train') | 8 | 1330 |
| ('8b', 'child', 'validation') | 2 | 332 |
| ('8b', 'child_prototypical', 'train') | 122 | 1126 |
| ('8b', 'child_prototypical', 'validation') | 40 | 361 |
| ('8c', 'child', 'train') | 8 | 1326 |
| ('8c', 'child', 'validation') | 2 | 331 |
| ('8c', 'child_prototypical', 'train') | 192 | 1547 |
| ('8c', 'child_prototypical', 'validation') | 30 | 210 |
| ('8d', 'child', 'train') | 8 | 1325 |
| ('8d', 'child', 'validation') | 2 | 331 |
| ('8d', 'child_prototypical', 'train') | 184 | 1472 |
| ('8d', 'child_prototypical', 'validation') | 50 | 438 |
| ('8e', 'child', 'train') | 8 | 1327 |
| ('8e', 'child', 'validation') | 2 | 331 |
| ('8e', 'child_prototypical', 'train') | 174 | 1340 |
| ('8e', 'child_prototypical', 'validation') | 36 | 270 |
| ('8f', 'child', 'train') | 8 | 1326 |
| ('8f', 'child', 'validation') | 2 | 331 |
| ('8f', 'child_prototypical', 'train') | 166 | 1416 |
| ('8f', 'child_prototypical', 'validation') | 56 | 452 |
| ('8g', 'child', 'train') | 8 | 1330 |
| ('8g', 'child', 'validation') | 2 | 332 |
| ('8g', 'child_prototypical', 'train') | 124 | 640 |
| ('8g', 'child_prototypical', 'validation') | 38 | 199 |
| ('8h', 'child', 'train') | 8 | 1324 |
| ('8h', 'child', 'validation') | 2 | 331 |
| ('8h', 'child_prototypical', 'train') | 200 | 1816 |
| ('8h', 'child_prototypical', 'validation') | 46 | 499 |
| ('9', 'parent', 'train') | 72 | 560 |
| ('9', 'parent', 'validation') | 18 | 140 |
| ('9a', 'child', 'train') | 8 | 1324 |
| ('9a', 'child', 'validation') | 2 | 331 |
| ('9a', 'child_prototypical', 'train') | 192 | 1520 |
| ('9a', 'child_prototypical', 'validation') | 54 | 426 |
| ('9b', 'child', 'train') | 8 | 1326 |
| ('9b', 'child', 'validation') | 2 | 331 |
| ('9b', 'child_prototypical', 'train') | 186 | 1783 |
| ('9b', 'child_prototypical', 'validation') | 36 | 307 |
| ('9c', 'child', 'train') | 8 | 1330 |
| ('9c', 'child', 'validation') | 2 | 332 |
| ('9c', 'child_prototypical', 'train') | 118 | 433 |
| ('9c', 'child_prototypical', 'validation') | 44 | 163 |
| ('9d', 'child', 'train') | 8 | 1328 |
| ('9d', 'child', 'validation') | 2 | 332 |
| ('9d', 'child_prototypical', 'train') | 156 | 1683 |
| ('9d', 'child_prototypical', 'validation') | 30 | 302 |
| ('9e', 'child', 'train') | 8 | 1329 |
| ('9e', 'child', 'validation') | 2 | 332 |
| ('9e', 'child_prototypical', 'train') | 132 | 1426 |
| ('9e', 'child_prototypical', 'validation') | 42 | 475 |
| ('9f', 'child', 'train') | 8 | 1328 |
| ('9f', 'child', 'validation') | 2 | 331 |
| ('9f', 'child_prototypical', 'train') | 158 | 1436 |
| ('9f', 'child_prototypical', 'validation') | 40 | 330 |
| ('9g', 'child', 'train') | 8 | 1324 |
| ('9g', 'child', 'validation') | 2 | 331 |
| ('9g', 'child_prototypical', 'train') | 200 | 1685 |
| ('9g', 'child_prototypical', 'validation') | 46 | 384 |
| ('9h', 'child', 'train') | 8 | 1325 |
| ('9h', 'child', 'validation') | 2 | 331 |
| ('9h', 'child_prototypical', 'train') | 190 | 1799 |
| ('9h', 'child_prototypical', 'validation') | 44 | 462 |
| ('9i', 'child', 'train') | 8 | 1328 |
| ('9i', 'child', 'validation') | 2 | 332 |
| ('9i', 'child_prototypical', 'train') | 158 | 1361 |
| ('9i', 'child_prototypical', 'validation') | 28 | 252 |
@inproceedings{jurgens-etal-2012-semeval,
title = "{S}em{E}val-2012 Task 2: Measuring Degrees of Relational Similarity",
author = "Jurgens, David and
Mohammad, Saif and
Turney, Peter and
Holyoak, Keith",
booktitle = "*{SEM} 2012: The First Joint Conference on Lexical and Computational Semantics {--} Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation ({S}em{E}val 2012)",
month = "7-8 " # jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S12-1047",
pages = "356--364",
}