The SimpleSearcher
class provides the entry point for searching.
Pyserini provides, out of the box, a pre-built index for TREC Disks 4 & 5, used in the TREC 2004 Robust Track:
from pyserini.search import SimpleSearcher
searcher = SimpleSearcher.from_prebuilt_index('robust04')
hits = searcher.search('hubble space telescope')
# Print the first 10 hits:
for i in range(0, 10):
print(f'{i+1:2} {hits[i].docid:15} {hits[i].score:.5f}')
The results should be as follows:
1 LA071090-0047 16.85690
2 FT934-5418 16.75630
3 FT921-7107 16.68290
4 LA052890-0021 16.37390
5 LA070990-0052 16.36460
6 LA062990-0180 16.19260
7 LA070890-0154 16.15610
8 FT934-2516 16.08950
9 LA041090-0148 16.08810
10 FT944-128 16.01920
To further examine the results:
# Grab the raw text:
hits[0].raw
# Grab the raw Lucene Document:
hits[0].lucene_document
Configure BM25 parameters and use RM3 query expansion:
searcher.set_bm25(0.9, 0.4)
searcher.set_rm3(10, 10, 0.5)
hits2 = searcher.search('hubble space telescope')
# Print the first 10 hits:
for i in range(0, 10):
print(f'{i+1:2} {hits2[i].docid:15} {hits2[i].score:.5f}')
If you want to perform a batch retrieval run, it's simple:
$ python -m pyserini.search --topics robust04 --index robust04 --output run.robust04.txt --bm25
And to evaluate using trec_eval
:
$ python -m pyserini.eval.trec_eval -m map -m P.30 robust04 run.robust04.txt
map all 0.2531
P_30 all 0.3102