Datasets:
Tasks:
Question Answering
Formats:
csv
Sub-tasks:
closed-domain-qa
Languages:
English
Size:
1M - 10M
License:
Update README.md
Browse files
README.md
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### Data Instances
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{
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"subject": "elephant",
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"predicate": "has_body_part"
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"score": 0.9999667967668732,
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"local_sigma": 1.0
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}
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### Data Fields
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- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99.
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## Dataset Creation
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See original paper.
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### Data Instances
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```python
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{
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"subject": "elephant",
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"predicate": "has_body_part"
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"score": 0.9999667967668732,
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"local_sigma": 1.0
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}
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```
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### Data Fields
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- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99.
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## Dataset Creation
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See original paper.
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