
Entity Disambiguation datasets as provided in the [GENRE](https://github.com/facebookresearch/GENRE/blob/main/scripts_genre/download_all_datasets.sh) repo. The dataset can be used to train and evaluate entity disambiguators.

The datasets can be imported easily as follows:

```
from datasets import load_dataset

ds = load_dataset("boragokbakan/entity_disambiguation", "aida")
```

Available dataset names are:
- `blink`
- `ace2004`
- `aida`
- `aquaint`
- `blink`
- `clueweb`
- `msnbc`
- `wiki`

**Note:** As the BLINK training set is very large in size (~10GB), it is advised to set `streaming=True` when calling `load_dataset`.
task_categories:question-answering language:en license:afl-3.0 entity disambiguation disambiguation ned GENRE BLINK region:us
{"language": ["en"], "license": "afl-3.0", "task_categories": ["question-answering"], "pretty_name": "Entity Disambiguation", "tags": ["entity disambiguation", "disambiguation", "ned", "GENRE", "BLINK"]}
TAGS
#task_categories-question-answering #language-English #license-afl-3.0 #entity disambiguation #disambiguation #ned #GENRE #BLINK #region-us 


Entity Disambiguation datasets as provided in the GENRE repo. The dataset can be used to train and evaluate entity disambiguators.

The datasets can be imported easily as follows:



Available dataset names are:
- 'blink'
- 'ace2004'
- 'aida'
- 'aquaint'
- 'blink'
- 'clueweb'
- 'msnbc'
- 'wiki'

Note: As the BLINK training set is very large in size (~10GB), it is advised to set 'streaming=True' when calling 'load_dataset'.
TAGS
#task_categories-question-answering #language-English #license-afl-3.0 #entity disambiguation #disambiguation #ned #GENRE #BLINK #region-us 
