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---
# 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
---
# scidocs.pisa
## Description
A PISA index for the SciDocs dataset
## Usage
```python
# Load the artifact
import pyterrier as pt
index = pt.Artifact.from_hf('pyterrier/scidocs.pisa')
index.bm25() # returns a BM25 retriever
```
## Benchmarks
| name | nDCG@10 | R@1000 |
|:-------|----------:|---------:|
| bm25 | 0.1504 | 0.5637 |
| dph | 0.1512 | 0.5701 |
## Reproduction
```python
import pyterrier as pt
from tqdm import tqdm
import ir_datasets
from pyterrier_pisa import PisaIndex
index = PisaIndex("scidocs.pisa", threads=16)
dataset = ir_datasets.load('beir/scidocs')
docs = ({'docno': d.doc_id, 'text': '{title}\n{text}'.format(**d._asdict())} for d in tqdm(dataset.docs))
index.index(docs)
```
## Metadata
```
{
"type": "sparse_index",
"format": "pisa",
"package_hint": "pyterrier-pisa",
"stemmer": "porter2"
}
```
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