size_categories:1K<n<10K language:en license:apache-2.0 region:us
---
license: apache-2.0
language:
- en
pretty_name: HAGRID
size_categories:
- 1K<n<10K
---
# HAGRID: A Human-LLM Collaborative Dataset for Generative Information-seeking with Attribution

HAGRID (**H**uman-in-the-loop **A**ttributable **G**enerative **R**etrieval for **I**nformation-seeking **D**ataset) 
is a dataset for generative information-seeking scenarios. 
It is constructed on top of MIRACL 🌍🙌🌏, an information retrieval dataset that consists of queries along with a set of manually labelled relevant passages (quotes).

## Dataset Structure
To load the dataset:
```python
import datasets
hagrid = datasets.load_dataset("miracl/hagrid", split="train")
print(hagrid[0])
```
It would show:
```json
{
  'query': ...,
  'query_id': ...,
    'quotes': [{               # a list of quotes that are manually labeled as relevant to the query
    'docid': ...,
    'idx': ...,
    'text': ...
    }, ...]
  'answers': [{
    'answer': ...,             # the complete answer generated by LLM
    'attributable': 1/0/None,  # 1: attributable; 0: unattributable; None: unlabeled
    'informative': 1/0,        # 1: informative; 0: uninformative
    'sentences': [{            # answers split into sentences
      'index': ...,
      'attributable': 0/1/None,
      'informative': 0/1/None,
      'text': ...,
    }, ...]
  }, ...]
}
```