This page documents regression experiments for the MS MARCO document ranking task, which is integrated into Anserini's regression testing framework. Note that there are four different regression conditions for this task, and this page describes the following:
- Indexing Condition: each MS MARCO document is first segmented into passages, each passage is treated as a unit of indexing
- Expansion Condition: none
In the passage indexing condition, we select the score of the highest-scoring passage from a document as the score for that document to produce a document ranking; this is known as the MaxP technique. All four conditions are described in detail here, in the context of doc2query-T5.
The exact configurations for these regressions are stored in this YAML file. Note that this page is automatically generated from this template as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.
Typical indexing command:
nohup sh target/appassembler/bin/IndexCollection -collection JsonCollection \
-input /path/to/msmarco-doc-per-passage \
-index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-generator DefaultLuceneDocumentGenerator \
-threads 1 -storePositions -storeDocvectors -storeRaw \
>& logs/log.msmarco-doc-per-passage &
The directory /path/to/msmarco-doc-per-passage/ should be a directory containing the segmented paragraph collection; see this link for how to prepare this collection.
For additional details, see explanation of common indexing options.
Topics and qrels are stored in src/main/resources/topics-and-qrels/.
The regression experiments here evaluate on the 5193 dev set questions.
After indexing has completed, you should be able to perform retrieval as follows:
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-default.topics.msmarco-doc.dev.txt \
-bm25 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-default+rm3.topics.msmarco-doc.dev.txt \
-bm25 -rm3 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-default+ax.topics.msmarco-doc.dev.txt \
-bm25 -axiom -axiom.deterministic -rerankCutoff 20 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-default+prf.topics.msmarco-doc.dev.txt \
-bm25 -bm25prf -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-tuned.topics.msmarco-doc.dev.txt \
-bm25 -bm25.k1 2.16 -bm25.b 0.61 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-tuned+rm3.topics.msmarco-doc.dev.txt \
-bm25 -bm25.k1 2.16 -bm25.b 0.61 -rm3 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-tuned+ax.topics.msmarco-doc.dev.txt \
-bm25 -bm25.k1 2.16 -bm25.b 0.61 -axiom -axiom.deterministic -rerankCutoff 20 -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
nohup target/appassembler/bin/SearchCollection -index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-topicreader TsvInt -topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-output runs/run.msmarco-doc-per-passage.bm25-tuned+prf.topics.msmarco-doc.dev.txt \
-bm25 -bm25.k1 2.16 -bm25.b 0.61 -bm25prf -hits 10000 -selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 1000 &
Evaluation can be performed using trec_eval:
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-default.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-default+rm3.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-default+ax.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-default+prf.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-tuned.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-tuned+rm3.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-tuned+ax.topics.msmarco-doc.dev.txt
tools/eval/trec_eval.9.0.4/trec_eval -m map -c -m recall.100 -c -m recall.1000 -c src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt runs/run.msmarco-doc-per-passage.bm25-tuned+prf.topics.msmarco-doc.dev.txt
With the above commands, you should be able to reproduce the following results:
| MAP | BM25 (default) | +RM3 | +Ax | +PRF | BM25 (tuned) | +RM3 | +Ax | +PRF |
|---|---|---|---|---|---|---|---|---|
| MS MARCO Doc: Dev | 0.2688 | 0.2416 | 0.2229 | 0.2325 | 0.2756 | 0.2443 | 0.2350 | 0.2271 |
| R@100 | BM25 (default) | +RM3 | +Ax | +PRF | BM25 (tuned) | +RM3 | +Ax | +PRF |
|---|---|---|---|---|---|---|---|---|
| MS MARCO Doc: Dev | 0.7849 | 0.7876 | 0.7703 | 0.7714 | 0.8009 | 0.7955 | 0.7909 | 0.7685 |
| R@1000 | BM25 (default) | +RM3 | +Ax | +PRF | BM25 (tuned) | +RM3 | +Ax | +PRF |
|---|---|---|---|---|---|---|---|---|
| MS MARCO Doc: Dev | 0.9180 | 0.9355 | 0.9266 | 0.9187 | 0.9311 | 0.9359 | 0.9341 | 0.9162 |
Explanation of settings:
- The setting "default" refers the default BM25 settings of
k1=0.9,b=0.4. - The setting "tuned" refers to
k1=2.16,b=0.61, tuned to optimize for recall@100 (i.e., for first-stage retrieval) on 2019/12.
In these runs, we are retrieving the top 1000 hits for each query and using trec_eval to evaluate all 1000 hits.
Since we're in the passage condition, we fetch the 10000 passages and select the top 1000 documents using MaxP.
This lets us measure R@100 and R@1000; the latter is particularly important when these runs are used as first-stage retrieval.
Beware, an official MS MARCO document ranking task leaderboard submission comprises only 100 hits per query.
See this page for details on Anserini baseline runs that were submitted to the official leaderboard.
The MaxP passage retrieval functionality is only available in SearchCollection; we use a simple script to convert the output back into the MS MARCO format for evaluation.
To generate an MS MARCO submission with the BM25 default parameters, corresponding to "BM25 (default)" above:
$ target/appassembler/bin/SearchCollection -topicreader TsvString \
-topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-output runs/run.msmarco-doc-per-passage.bm25-default.trec \
-bm25 -bm25.k1 0.9 -bm25.b 0.4 -hits 1000 \
-selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 100
$ python tools/scripts/msmarco/convert_trec_to_msmarco_run.py \
--input runs/run.msmarco-doc-per-passage.bm25-default.trec \
--output runs/run.msmarco-doc-per-passage.bm25-default.txt
$ python tools/scripts/msmarco/msmarco_doc_eval.py \
--judgments src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt \
--run runs/run.msmarco-doc-per-passage.bm25-default.txt
#####################
MRR @100: 0.2682349308946578
QueriesRanked: 5193
#####################This run was not submitted to the MS MARCO document ranking leaderboard, but is reported in the Lin et al. (SIGIR 2021) Pyserini paper.
To generate an MS MARCO submission with the BM25 tuned parameters, corresponding to "BM25 (tuned)" above:
$ target/appassembler/bin/SearchCollection -topicreader TsvString \
-topics src/main/resources/topics-and-qrels/topics.msmarco-doc.dev.txt \
-index indexes/lucene-index.msmarco-doc-per-passage.pos+docvectors+raw \
-output runs/run.msmarco-doc-per-passage.bm25-tuned.trec \
-bm25 -bm25.k1 2.16 -bm25.b 0.61 -hits 1000 \
-selectMaxPassage -selectMaxPassage.delimiter "#" -selectMaxPassage.hits 100
$ python tools/scripts/msmarco/convert_trec_to_msmarco_run.py \
--input runs/run.msmarco-doc-per-passage.bm25-tuned.trec \
--output runs/run.msmarco-doc-per-passage.bm25-tuned.txt
$ python tools/scripts/msmarco/msmarco_doc_eval.py \
--judgments src/main/resources/topics-and-qrels/qrels.msmarco-doc.dev.txt \
--run runs/run.msmarco-doc-per-passage.bm25-tuned.txt
#####################
MRR @100: 0.2751202109946902
QueriesRanked: 5193
#####################This run corresponds to the MS MARCO document ranking leaderboard entry "Anserini's BM25 (per passage), parameters tuned for recall@100 (k1=2.16, b=0.61)" dated 2021/01/20, and is reported in the Lin et al. (SIGIR 2021) Pyserini paper.