dl23-doc.yaml

---
corpus: msmarco-v2-doc
corpus_path: collections/msmarco/msmarco_v2_doc/

index_path: indexes/lucene-inverted.msmarco-v2-doc/
collection_class: MsMarcoV2DocCollection
generator_class: DefaultLuceneDocumentGenerator
index_threads: 24
index_options: -storeRaw
index_stats:
  documents: 11959635
  documents (non-empty): 11959635
  total terms: 14165667143

metrics:
  - metric: MAP@100
    command: bin/trec_eval
    params: -c -M 100 -m map
    separator: "\t"
    parse_index: 2
    metric_precision: 4
    can_combine: no
  - metric: MRR@100
    command: bin/trec_eval
    params: -c -M 100 -m recip_rank
    separator: "\t"
    parse_index: 2
    metric_precision: 4
    can_combine: true
  - metric: nDCG@10
    command: bin/trec_eval
    params: -c -m ndcg_cut.10
    separator: "\t"
    parse_index: 2
    metric_precision: 4
    can_combine: true
  - metric: R@100
    command: bin/trec_eval
    params: -c -m recall.100
    separator: "\t"
    parse_index: 2
    metric_precision: 4
    can_combine: false
  - metric: R@1000
    command: bin/trec_eval
    params: -c -m recall.1000
    separator: "\t"
    parse_index: 2
    metric_precision: 4
    can_combine: false

topic_reader: TsvInt
topics:
  - name: "[DL23 (Doc)](https://microsoft.github.io/msmarco/TREC-Deep-Learning)"
    id: dl23
    path: topics.dl23.txt
    qrel: qrels.dl23-doc.txt

models:
  - name: bm25-default
    display: BM25 (default)
    params: -hits 1000 -bm25
    results:
      MAP@100:
        - 0.1046
      MRR@100:
        - 0.5669
      nDCG@10:
        - 0.2946
      R@100:
        - 0.2422
      R@1000:
        - 0.5262
  - name: bm25-default+rm3
    display: +RM3
    params: -hits 1000 -bm25 -rm3 -collection MsMarcoV2DocCollection
    results:
      MAP@100:
        - 0.1174
      MRR@100:
        - 0.4518
      nDCG@10:
        - 0.2462
      R@100:
        - 0.2585
      R@1000:
        - 0.5232
  - name: bm25-default+rocchio
    display: +Rocchio
    params: -hits 1000 -bm25 -rocchio -collection MsMarcoV2DocCollection
    results:
      MAP@100:
        - 0.1219
      MRR@100:
        - 0.5045
      nDCG@10:
        - 0.2619
      R@100:
        - 0.2651
      R@1000:
        - 0.5385