Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
relation extraction
License:
Update README.md
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README.md
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### Data Instances
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#### kbp37
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An example of 'train' looks as follows:
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```json
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{
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```
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#### kbp37_formatted
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An example of 'train' looks as follows:
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```json
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{
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#### kbp37
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- `id`: the instance id of this sentence, a `string` feature.
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- `sentence`: the sentence, a `string` features.
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- `relation`: the relation label of this instance,
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#### kbp37_formatted
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- `id`: the instance id of this sentence, a `string` feature.
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- `subj_end`: the 0-based index of the end token of the relation subject mention, exclusive, an `ìnt` feature.
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- `obj_start`: the 0-based index of the start token of the relation object mention, an `ìnt` feature.
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- `obj_end`: the 0-based index of the end token of the relation object mention, exclusive, an `ìnt` feature.
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- `relation`: the relation label of this instance,
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### Data Splits
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### Data Instances
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#### kbp37
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- **Size of downloaded dataset files:** 5.11 MB
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- **Size of the generated dataset:** 4.7 MB
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An example of 'train' looks as follows:
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```json
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{
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```
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#### kbp37_formatted
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- **Size of downloaded dataset files:** 5.11 MB
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- **Size of the generated dataset:** 6.58 MB
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An example of 'train' looks as follows:
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```json
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{
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#### kbp37
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- `id`: the instance id of this sentence, a `string` feature.
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- `sentence`: the sentence, a `string` features.
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- `relation`: the relation label of this instance, an `int` classification label.
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```python
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{"no_relation": 0, "org:alternate_names(e1,e2)": 1, "org:alternate_names(e2,e1)": 2, "org:city_of_headquarters(e1,e2)": 3, "org:city_of_headquarters(e2,e1)": 4, "org:country_of_headquarters(e1,e2)": 5, "org:country_of_headquarters(e2,e1)": 6, "org:founded(e1,e2)": 7, "org:founded(e2,e1)": 8, "org:founded_by(e1,e2)": 9, "org:founded_by(e2,e1)": 10, "org:members(e1,e2)": 11, "org:members(e2,e1)": 12, "org:stateorprovince_of_headquarters(e1,e2)": 13, "org:stateorprovince_of_headquarters(e2,e1)": 14, "org:subsidiaries(e1,e2)": 15, "org:subsidiaries(e2,e1)": 16, "org:top_members/employees(e1,e2)": 17, "org:top_members/employees(e2,e1)": 18, "per:alternate_names(e1,e2)": 19, "per:alternate_names(e2,e1)": 20, "per:cities_of_residence(e1,e2)": 21, "per:cities_of_residence(e2,e1)": 22, "per:countries_of_residence(e1,e2)": 23, "per:countries_of_residence(e2,e1)": 24, "per:country_of_birth(e1,e2)": 25, "per:country_of_birth(e2,e1)": 26, "per:employee_of(e1,e2)": 27, "per:employee_of(e2,e1)": 28, "per:origin(e1,e2)": 29, "per:origin(e2,e1)": 30, "per:spouse(e1,e2)": 31, "per:spouse(e2,e1)": 32, "per:stateorprovinces_of_residence(e1,e2)": 33, "per:stateorprovinces_of_residence(e2,e1)": 34, "per:title(e1,e2)": 35, "per:title(e2,e1)": 36}
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```
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#### kbp37_formatted
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- `id`: the instance id of this sentence, a `string` feature.
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- `subj_end`: the 0-based index of the end token of the relation subject mention, exclusive, an `ìnt` feature.
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- `obj_start`: the 0-based index of the start token of the relation object mention, an `ìnt` feature.
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- `obj_end`: the 0-based index of the end token of the relation object mention, exclusive, an `ìnt` feature.
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- `relation`: the relation label of this instance, an `int` classification label (same as `'kbp37''`).
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### Data Splits
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