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Anserini Regressions: NeuCLIR22 — Persian (Document Translation)

This page presents document translation regression experiments for the TREC 2022 NeuCLIR Track, Persian, with the following configuration:

  • Queries: English
  • Documents: Machine-translated documents from Persian into English (corpus provided by the organizers)
  • Model: SPLADE CoCondenser SelfDistil

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.

We make available a version of the corpus that has already been encoded with SPLADE CoCondenser SelfDistil, i.e., we performed model inference on every document and stored the output sparse vectors. Thus, no neural inference is required to reproduce these experiments; see instructions below.

From one of our Waterloo servers (e.g., orca), the following command will perform the complete regression, end to end:

python src/main/python/run_regression.py --index --verify --search --regression neuclir22-fa-dt-splade

Corpus Download

Download the corpus and unpack into collections/:

wget https://rgw.cs.uwaterloo.ca/pyserini/data/neuclir22-fa-en-splade.tar -P collections/
tar xvf collections/neuclir22-fa-en-splade.tar -C collections/

To confirm, neuclir22-fa-en-splade.tar is 2.8 GB and has MD5 checksum 186d4b7025c4915cf9a33371c4ef37c5. With the corpus downloaded, the following command will perform the remaining steps below:

python src/main/python/run_regression.py --index --verify --search --regression neuclir22-fa-dt-splade \
  --corpus-path collections/neuclir22-fa-en-splade

Indexing

Typical indexing command:

bin/run.sh io.anserini.index.IndexCollection \
  -threads 8 \
  -collection JsonVectorCollection \
  -input /path/to/neuclir22-fa-en-splade \
  -generator DefaultLuceneDocumentGenerator \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -impact -pretokenized -storeRaw \
  >& logs/log.neuclir22-fa-en-splade &

For additional details, see explanation of common indexing options.

Retrieval

After indexing has completed, you should be able to perform retrieval as follows:

bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-title.txt \
  -impact -pretokenized &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc.txt \
  -impact -pretokenized &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc_title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc_title.txt \
  -impact -pretokenized &

bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-title.txt \
  -impact -pretokenized -rm3 -collection JsonVectorCollection &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc.txt \
  -impact -pretokenized -rm3 -collection JsonVectorCollection &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc_title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc_title.txt \
  -impact -pretokenized -rm3 -collection JsonVectorCollection &

bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-title.txt \
  -impact -pretokenized -rocchio -collection JsonVectorCollection &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc.txt \
  -impact -pretokenized -rocchio -collection JsonVectorCollection &
bin/run.sh io.anserini.search.SearchCollection \
  -index indexes/lucene-index.neuclir22-fa-en-splade \
  -topics tools/topics-and-qrels/topics.neuclir22-en.splade.original-desc_title.txt.gz \
  -topicReader TsvInt \
  -output runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc_title.txt \
  -impact -pretokenized -rocchio -collection JsonVectorCollection &

Evaluation can be performed using trec_eval:

bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc_title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade.topics.neuclir22-en.splade.original-desc_title.txt

bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc_title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rm3.topics.neuclir22-en.splade.original-desc_title.txt

bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-title.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc.txt
bin/trec_eval -c -m ndcg_cut.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc_title.txt
python -m pyserini.eval.trec_eval -c -m judged.20 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m recall.1000 tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc_title.txt
bin/trec_eval -c -m map tools/topics-and-qrels/qrels.neuclir22-fa.txt runs/run.neuclir22-fa-en-splade.splade+rocchio.topics.neuclir22-en.splade.original-desc_title.txt

Effectiveness

With the above commands, you should be able to reproduce the following results:

MAP SPLADE +RM3 +Rocchio
NeuCLIR 2022 (Persian): title (original English queries) 0.2977 0.2800 0.2835
NeuCLIR 2022 (Persian): desc (original English queries) 0.3057 0.2956 0.3275
NeuCLIR 2022 (Persian): desc+title (original English queries) 0.3203 0.3002 0.3267
nDCG@20 SPLADE +RM3 +Rocchio
NeuCLIR 2022 (Persian): title (original English queries) 0.4627 0.4258 0.4438
NeuCLIR 2022 (Persian): desc (original English queries) 0.4618 0.4480 0.4675
NeuCLIR 2022 (Persian): desc+title (original English queries) 0.4802 0.4477 0.4645
J@20 SPLADE +RM3 +Rocchio
NeuCLIR 2022 (Persian): title (original English queries) 0.3768 0.3496 0.3781
NeuCLIR 2022 (Persian): desc (original English queries) 0.3882 0.3504 0.3860
NeuCLIR 2022 (Persian): desc+title (original English queries) 0.3917 0.3610 0.3908
Recall@1000 SPLADE +RM3 +Rocchio
NeuCLIR 2022 (Persian): title (original English queries) 0.8478 0.8018 0.8592
NeuCLIR 2022 (Persian): desc (original English queries) 0.8796 0.8061 0.8735
NeuCLIR 2022 (Persian): desc+title (original English queries) 0.8860 0.7948 0.8703

Reproduction Log*

To add to this reproduction log, modify this template and run bin/build.sh to rebuild the documentation.