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--- |
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tags: |
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- pyterrier |
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- pyterrier-artifact |
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- pyterrier-artifact.sparse_index |
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- pyterrier-artifact.sparse_index.pisa |
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task_categories: |
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- text-retrieval |
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viewer: false |
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--- |
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# fiqa.pisa |
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## Description |
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A PISA index for the FIQA dataset |
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## Usage |
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```python |
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# Load the artifact |
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import pyterrier as pt |
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index = pt.Artifact.from_hf('pyterrier/fiqa.pisa') |
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index.bm25() # returns a BM25 retriever |
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``` |
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## Benchmarks |
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`fiqa/dev` |
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| name | nDCG@10 | R@1000 | |
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|:-------|----------:|---------:| |
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| bm25 | 0.263 | 0.7423 | |
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| dph | 0.2587 | 0.7497 | |
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`fiqa/test` |
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| name | nDCG@10 | R@1000 | |
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|:-------|----------:|---------:| |
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| bm25 | 0.2411 | 0.7504 | |
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| dph | 0.2401 | 0.7615 | |
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## Reproduction |
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```python |
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import pyterrier as pt |
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from tqdm import tqdm |
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import ir_datasets |
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from pyterrier_pisa import PisaIndex |
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index = PisaIndex("fiqa.pisa", threads=16) |
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dataset = ir_datasets.load('beir/fiqa') |
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docs = ({'docno': d.doc_id, 'text': d.default_text()} for d in tqdm(dataset.docs)) |
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index.index(docs) |
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``` |
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## Metadata |
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``` |
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{ |
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"type": "sparse_index", |
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"format": "pisa", |
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"package_hint": "pyterrier-pisa", |
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"stemmer": "porter2" |
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} |
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``` |
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