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README.md
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#
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## Description
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## Usage
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```python
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```
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## Benchmarks
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## Reproduction
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```python
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```
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## Metadata
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viewer: false
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# MS MARCO PISA Index
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## Description
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This is an index of the MS MARCO passage (v1) dataset with PISA. It can be used for passage retrieval using lexical methods.
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## Usage
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```python
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>>> from pyterrier_pisa import PisaIndex
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>>> index = PisaIndex.from_hf('macavaney/msmarco-passage.pisa')
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>>> bm25 = index.bm25()
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>>> bm25.search('terrier breeds')
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qid query docno score rank
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0 1 terrier breeds 1406578 22.686367 0
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1 1 terrier breeds 5785957 22.611134 1
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2 1 terrier breeds 7455374 22.592781 2
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3 1 terrier breeds 3984886 22.242958 3
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4 1 terrier breeds 3984893 22.009525 4
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...
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```
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## Benchmarks
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**TREC DL 2019**
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<details>
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<summary>Code</summary>
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```python
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from ir_measures import nDCG, RR, MAP, R
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import pyterrier as pt
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from pyterrier_pisa import PisaIndex
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index = PisaIndex.from_hf('macavaney/msmarco-passage.pisa')
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dataset = pt.get_dataset('irds:msmarco-passage/trec-dl-2019/judged')
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pt.Experiment(
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[index.bm25(), index.qld(), index.dph(), index.pl2()],
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dataset.get_topics(),
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dataset.get_qrels(),
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[nDCG@10, nDCG, RR(rel=2), MAP(rel=2), R(rel=2)@1000],
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['BM25', 'QLD', 'DPH', 'PL2'],
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round=4,
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)
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```
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</details>
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| | name | nDCG@10 | nDCG | RR(rel=2) | AP(rel=2) | R(rel=2)@1000 |
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|---:|:-------|----------:|-------:|------------:|------------:|----------------:|
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| 0 | BM25 | 0.4989 | 0.6023 | 0.6804 | 0.3031 | 0.7555 |
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| 1 | QLD | 0.468 | 0.5984 | 0.6047 | 0.3037 | 0.7601 |
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| 2 | DPH | 0.4975 | 0.5907 | 0.6674 | 0.3009 | 0.7436 |
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| 3 | PL2 | 0.4503 | 0.5681 | 0.6495 | 0.2679 | 0.7304 |
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**TREC DL 2020**
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<details>
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<summary>Code</summary>
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```python
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from ir_measures import nDCG, RR, MAP, R
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import pyterrier as pt
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from pyterrier_pisa import PisaIndex
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index = PisaIndex.from_hf('macavaney/msmarco-passage.pisa')
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dataset = pt.get_dataset('irds:msmarco-passage/trec-dl-2020/judged')
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pt.Experiment(
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[index.bm25(), index.qld(), index.dph(), index.pl2()],
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dataset.get_topics(),
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dataset.get_qrels(),
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[nDCG@10, nDCG, RR(rel=2), MAP(rel=2), R(rel=2)@1000],
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['BM25', 'QLD', 'DPH', 'PL2'],
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round=4,
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)
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```
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</details>
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| | name | nDCG@10 | nDCG | RR(rel=2) | AP(rel=2) | R(rel=2)@1000 |
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|---:|:-------|----------:|-------:|------------:|------------:|----------------:|
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| 0 | BM25 | 0.4793 | 0.5963 | 0.6529 | 0.2974 | 0.8048 |
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| 1 | QLD | 0.4511 | 0.587 | 0.5812 | 0.2879 | 0.8125 |
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| 2 | DPH | 0.4586 | 0.5704 | 0.6123 | 0.2779 | 0.798 |
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| 3 | PL2 | 0.4552 | 0.5609 | 0.5788 | 0.2666 | 0.7772 |
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**MS MARCO Dev (small)**
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<details>
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<summary>Code</summary>
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```python
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from ir_measures import RR, R
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import pyterrier as pt
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from pyterrier_pisa import PisaIndex
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index = PisaIndex.from_hf('macavaney/msmarco-passage.pisa')
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dataset = pt.get_dataset('irds:msmarco-passage/dev/small')
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pt.Experiment(
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[index.bm25(), index.qld(), index.dph(), index.pl2()],
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dataset.get_topics(),
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dataset.get_qrels(),
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[RR@10, R@1000],
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['BM25', 'QLD', 'DPH', 'PL2'],
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round=4,
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)
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```
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</details>
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## Reproduction
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```python
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>>> import pyterrier_pisa
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>>> import pyterrier as pt
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>>> idx = pyterrier_pisa.PisaIndex('msmarco-passage.pisa')
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>>> idx.indexer().index(pt.get_dataset('irds:msmarco-passage').get_corpus_iter())
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```
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## Metadata
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