research-backup/roberta-large-semeval2012-v2-average-prompt-c-nce
Feature Extraction • Updated • 21
relation_type stringlengths 1 3 | positives sequence | negatives sequence |
|---|---|---|
4a | [
[
"rich",
"poor"
],
[
"smooth",
"rough"
],
[
"cooked",
"raw"
],
[
"happy",
"sad"
],
[
"fat",
"thin"
],
[
"dry",
"wet"
],
[
"hot",
"cold"
],
[
"full",
"empty"
]
] | [
[
"smile",
"happiness"
],
[
"cross",
"christianity"
],
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
... |
5e | [
[
"chef",
"cook"
],
[
"pastor",
"preach"
],
[
"heart",
"beat"
],
[
"lion",
"roar"
],
[
"fire",
"burn"
],
[
"dynamite",
"explode"
],
[
"dog",
"bark"
],
[
"tailor",
"sew"
]
] | [
[
"cross",
"christianity"
],
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapo... |
8b | [
[
"heat",
"sweat"
],
[
"fright",
"scream"
],
[
"danger",
"flee"
],
[
"dirtiness",
"bathe"
],
[
"happiness",
"smile"
],
[
"coldness",
"shiver"
],
[
"tiredness",
"rest"
],
[
"thirsty",
"drink"
]
] | [
[
"cross",
"christianity"
],
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapo... |
9f | [
[
"winter",
"sledding"
],
[
"morning",
"sunrise"
],
[
"autumn",
"equinox"
],
[
"adolescence",
"puberty"
],
[
"winter",
"christmas"
],
[
"birthday",
"celebration"
],
[
"winter",
"cold"
],
[
"morning",
"breakfast"
]
] | [
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
... |
10c | [
[
"acknowledgement",
"signature"
],
[
"sound",
"recording"
],
[
"landscape",
"photo"
],
[
"book",
"summary"
],
[
"event",
"documentary"
],
[
"ideal",
"fairytale"
],
[
"achievement",
"trophy"
],
[
"image",
"photograph"
]
] | [
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
... |
10b | [
[
"laughter",
"amusement"
],
[
"tears",
"sorrow"
],
[
"laugh",
"amusement"
],
[
"tear",
"sadness"
],
[
"crying",
"sadness"
],
[
"nod",
"agreement"
],
[
"groan",
"pain"
],
[
"tears",
"sadness"
]
] | [
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
... |
9g | [
[
"childhood",
"crayon"
],
[
"puberty",
"hormones"
],
[
"adulthood",
"job"
],
[
"girlhood",
"dolls"
],
[
"morning",
"sunrise"
],
[
"infancy",
"bottle"
],
[
"death",
"coffin"
],
[
"infancy",
"pacifier"
]
] | [
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
],
[
"birth",
"death"
... |
8c | [
[
"battery",
"laptop"
],
[
"mouse",
"computer"
],
[
"electricity",
"tv"
],
[
"oil",
"lamp"
],
[
"electricity",
"lamp"
],
[
"battery",
"flashlight"
],
[
"electricity",
"television"
],
[
"bullet",
"gun"
]
] | [
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
],
[
"birth",
"death"
... |
5d | [
[
"sad",
"depression"
],
[
"lethargic",
"fatigue"
],
[
"tired",
"exhaustion"
],
[
"starving",
"hunger"
],
[
"drunk",
"intoxication"
],
[
"yelling",
"anger"
],
[
"lazy",
"indolence"
],
[
"thoughtful",
"contemplation"
]
] | [
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
... |
6h | [
[
"polish",
"tarnished"
],
[
"enlighten",
"ignorant"
],
[
"sharpen",
"dull"
],
[
"fill",
"empty"
],
[
"groom",
"unkempt"
],
[
"heat",
"frozen"
],
[
"repair",
"damaged"
],
[
"wash",
"dirty"
]
] | [
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
... |
5f | [
[
"rotten",
"stink"
],
[
"fragile",
"break"
],
[
"healthy",
"survive"
],
[
"buoyant",
"float"
],
[
"malleable",
"bend"
],
[
"pliable",
"bend"
],
[
"unstable",
"fall"
],
[
"happy",
"smile"
]
] | [
[
"cross",
"christianity"
],
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapo... |
4b | [
[
"bad",
"good"
],
[
"tall",
"short"
],
[
"dark",
"light"
],
[
"big",
"small"
],
[
"difficult",
"easy"
],
[
"black",
"white"
],
[
"accept",
"reject"
],
[
"fast",
"slow"
]
] | [
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
... |
9e | [
[
"river",
"bank"
],
[
"bank",
"river"
],
[
"stream",
"bank"
],
[
"sidewalk",
"yard"
],
[
"sill",
"window"
],
[
"guardrail",
"highway"
],
[
"margin",
"paper"
],
[
"ditch",
"road"
]
] | [
[
"crossbones",
"poison"
],
[
"diploma",
"education"
],
[
"smile",
"happiness"
],
[
"cross",
"christianity"
],
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"c... |
8a | [
[
"bath",
"cleanliness"
],
[
"explosion",
"damage"
],
[
"injury",
"pain"
],
[
"exercise",
"fitness"
],
[
"tragedy",
"tears"
],
[
"disease",
"sickness"
],
[
"germs",
"sickness"
],
[
"loss",
"grief"
]
] | [
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
],
[
"kitchen",
"oven"
],
[
"praise",
"criticize"
... |
10a | [
[
"license",
"permission"
],
[
"sign",
"direction"
],
[
"smoke",
"fire"
],
[
"crown",
"royalty"
],
[
"crossbones",
"poison"
],
[
"diploma",
"education"
],
[
"smile",
"happiness"
],
[
"cross",
"christianity"
]
] | [
[
"garage",
"wrench"
],
[
"office",
"telephone"
],
[
"library",
"book"
],
[
"playground",
"slide"
],
[
"casino",
"cards"
],
[
"kitchen",
"pot"
],
[
"office",
"desk"
],
[
"war",
"weapon"
],
[
"office",
"computer"
... |
End of preview. Expand in Data Studio
Dataset Card for "relbert/semeval2012_relational_similarity_v2"
Dataset Summary
IMPORTANT: This is the same dataset as relbert/semeval2012_relational_similarity, but with a different train/validation split.
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.
Dataset Structure
Data Instances
An example of train looks as follows.
{
'relation_type': '8d',
'positives': [ [ "breathe", "live" ], [ "study", "learn" ], [ "speak", "communicate" ], ... ]
'negatives': [ [ "starving", "hungry" ], [ "clean", "bathe" ], [ "hungry", "starving" ], ... ]
}
Data Splits
| name | train | validation |
|---|---|---|
| semeval2012_relational_similarity_v2 | 89 | 89 |
Number of Positive/Negative Word-pairs in each Split
| relation_type | positive (train) | negative (train) | positive (validation) | negative (validation) |
|---|---|---|---|---|
| 1 | 40 | 592 | 10 | 148 |
| 10 | 48 | 584 | 12 | 146 |
| 10a | 8 | 640 | 2 | 159 |
| 10b | 8 | 638 | 2 | 159 |
| 10c | 8 | 640 | 2 | 160 |
| 10d | 8 | 640 | 2 | 159 |
| 10e | 8 | 636 | 2 | 159 |
| 10f | 8 | 640 | 2 | 159 |
| 1a | 8 | 638 | 2 | 159 |
| 1b | 8 | 638 | 2 | 159 |
| 1c | 8 | 640 | 2 | 160 |
| 1d | 8 | 638 | 2 | 159 |
| 1e | 8 | 636 | 2 | 158 |
| 2 | 80 | 552 | 20 | 138 |
| 2a | 8 | 640 | 2 | 159 |
| 2b | 8 | 637 | 2 | 159 |
| 2c | 8 | 639 | 2 | 159 |
| 2d | 8 | 639 | 2 | 159 |
| 2e | 8 | 640 | 2 | 159 |
| 2f | 8 | 642 | 2 | 160 |
| 2g | 8 | 637 | 2 | 159 |
| 2h | 8 | 640 | 2 | 159 |
| 2i | 8 | 640 | 2 | 160 |
| 2j | 8 | 641 | 2 | 160 |
| 3 | 64 | 568 | 16 | 142 |
| 3a | 8 | 640 | 2 | 159 |
| 3b | 8 | 642 | 2 | 160 |
| 3c | 8 | 639 | 2 | 159 |
| 3d | 8 | 639 | 2 | 159 |
| 3e | 8 | 642 | 2 | 160 |
| 3f | 8 | 643 | 2 | 160 |
| 3g | 8 | 641 | 2 | 160 |
| 3h | 8 | 641 | 2 | 160 |
| 4 | 64 | 568 | 16 | 142 |
| 4a | 8 | 642 | 2 | 160 |
| 4b | 8 | 638 | 2 | 159 |
| 4c | 8 | 640 | 2 | 160 |
| 4d | 8 | 637 | 2 | 159 |
| 4e | 8 | 642 | 2 | 160 |
| 4f | 8 | 642 | 2 | 160 |
| 4g | 8 | 639 | 2 | 159 |
| 4h | 8 | 641 | 2 | 160 |
| 5 | 72 | 560 | 18 | 140 |
| 5a | 8 | 639 | 2 | 159 |
| 5b | 8 | 641 | 2 | 160 |
| 5c | 8 | 640 | 2 | 159 |
| 5d | 8 | 638 | 2 | 159 |
| 5e | 8 | 641 | 2 | 160 |
| 5f | 8 | 641 | 2 | 160 |
| 5g | 8 | 642 | 2 | 160 |
| 5h | 8 | 640 | 2 | 160 |
| 5i | 8 | 640 | 2 | 160 |
| 6 | 64 | 568 | 16 | 142 |
| 6a | 8 | 639 | 2 | 159 |
| 6b | 8 | 641 | 2 | 160 |
| 6c | 8 | 641 | 2 | 160 |
| 6d | 8 | 644 | 2 | 160 |
| 6e | 8 | 641 | 2 | 160 |
| 6f | 8 | 640 | 2 | 159 |
| 6g | 8 | 639 | 2 | 159 |
| 6h | 8 | 640 | 2 | 159 |
| 7 | 64 | 568 | 16 | 142 |
| 7a | 8 | 640 | 2 | 160 |
| 7b | 8 | 637 | 2 | 159 |
| 7c | 8 | 638 | 2 | 159 |
| 7d | 8 | 640 | 2 | 160 |
| 7e | 8 | 638 | 2 | 159 |
| 7f | 8 | 637 | 2 | 159 |
| 7g | 8 | 636 | 2 | 158 |
| 7h | 8 | 636 | 2 | 159 |
| 8 | 64 | 568 | 16 | 142 |
| 8a | 8 | 638 | 2 | 159 |
| 8b | 8 | 641 | 2 | 160 |
| 8c | 8 | 637 | 2 | 159 |
| 8d | 8 | 637 | 2 | 159 |
| 8e | 8 | 637 | 2 | 159 |
| 8f | 8 | 638 | 2 | 159 |
| 8g | 8 | 635 | 2 | 158 |
| 8h | 8 | 639 | 2 | 159 |
| 9 | 72 | 560 | 18 | 140 |
| 9a | 8 | 636 | 2 | 159 |
| 9b | 8 | 640 | 2 | 159 |
| 9c | 8 | 632 | 2 | 158 |
| 9d | 8 | 643 | 2 | 160 |
| 9e | 8 | 644 | 2 | 160 |
| 9f | 8 | 640 | 2 | 159 |
| 9g | 8 | 637 | 2 | 159 |
| 9h | 8 | 640 | 2 | 159 |
| 9i | 8 | 640 | 2 | 159 |
| SUM | 1264 | 56198 | 316 | 14009 |
Citation Information
@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",
}
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Repository:
RelBERT
Paper:
aclanthology.org
Dataset:
SemEval2012: Relational Similarity
Number of rows:
178
Total file size:
1.64 MB