task_categories:text-retrieval region:us pyterrier pyterrier-artifact pyterrier-artifact.sparse_index pyterrier-artifact.sparse_index.pisa
---
# pretty_name: "" # Example: "MS MARCO Terrier Index"
tags:
- pyterrier
- pyterrier-artifact
- pyterrier-artifact.sparse_index
- pyterrier-artifact.sparse_index.pisa
task_categories:
- text-retrieval
viewer: false
---

# hotpotqa.pisa

## Description

A PISA index for the Hotpot QA dataset

## Usage

```python
# Load the artifact
import pyterrier as pt
index = pt.Artifact.from_hf('pyterrier/hotpotqa.pisa')
index.bm25() # returns a BM25 retriever
```

## Benchmarks

`hotpotqa/dev`

| name   |   nDCG@10 |   R@1000 |
|:-------|----------:|---------:|
| bm25   |    0.6525 |   0.8909 |
| dph    |    0.6445 |   0.8888 |

`hotpotqa/test`

| name   |   nDCG@10 |   R@1000 |
|:-------|----------:|---------:|
| bm25   |    0.6318 |   0.8851 |
| dph    |    0.6246 |   0.8837 |


## Reproduction

```python
import pyterrier as pt
from tqdm import tqdm
import ir_datasets
from pyterrier_pisa import PisaIndex
index = PisaIndex("hotpotqa.pisa", threads=16)
dataset = ir_datasets.load('beir/hotpotqa')
docs = ({'docno': d.doc_id, 'text': d.default_text()} for d in tqdm(dataset.docs))
index.index(docs)
```

## Metadata

```
{
  "type": "sparse_index",
  "format": "pisa",
  "package_hint": "pyterrier-pisa",
  "stemmer": "porter2"
}
```
