Datasets:

FOR-sight-ai
/

ECSS-1.0

dataset_info:
  - config_name: corpus
    features:
      - name: _id
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
      - name: metadata
        struct:
          - name: document_id
            dtype: string
          - name: page_number
            dtype: int64
      - name: image
        dtype: 'null'
    splits:
      - name: test
        num_bytes: 43537055
        num_examples: 22700
    download_size: 17741057
    dataset_size: 43537055
  - config_name: corpus-with-image
    features:
      - name: _id
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
      - name: metadata
        struct:
          - name: document_id
            dtype: string
          - name: page_number
            dtype: int64
      - name: image
        dtype: image
    splits:
      - name: test
        num_bytes: 2295554066
        num_examples: 22700
    download_size: 2267597419
    dataset_size: 2295554066
  - config_name: queries
    features:
      - name: _id
        dtype: string
      - name: query_text
        dtype: string
      - name: relevant_document_ids
        list:
          - name: corpus_id
            dtype: string
          - name: metadata
            struct:
              - name: document_id
                dtype: string
              - name: page_number
                dtype: int64
              - name: question_type
                dtype: string
          - name: score
            dtype: float64
    splits:
      - name: test
        num_bytes: 16544
        num_examples: 67
    download_size: 9270
    dataset_size: 16544
configs:
  - config_name: corpus
    data_files:
      - split: test
        path: corpus/test-*
  - config_name: corpus-with-image
    data_files:
      - split: test
        path: corpus-with-image/test-*
  - config_name: queries
    data_files:
      - split: test
        path: queries/test-*

ECSS-1.0 Dataset

Dataset Summary

This dataset provides a focused benchmark for retrieval and generation tasks related to ECSS (European Cooperation for Space Standardization) documents. It includes a set of documents, queries, relevance judgments (qrels), and page images.

Number of Documents: 196
Number of Queries: 67
Number of Pages: 22700
Number of Relevance Judgments (qrels): 89
Average Number of Pages per Query: 1.3

Dataset Structure (Hugging Face Datasets)

The dataset is structured into the following subsets:

corpus: Contains page-level information:
- _id: A unique identifier for this specific page within the corpus.
- title: The title of the document.
- text: The text of the document.
queries: Contains query information:
- _id: Unique identifier for the question.
- query_text: The question text.
- relevant_document_ids: A list of corpus documents considered as references for this question, each reference containing:
  - corpus_id: The document identifier.
  - score: The importance or relevance score.

Usage Examples

You can load the datasets using the load_from_disk function from the datasets library. Replace the paths with the actual locations on your machine.

from datasets import load_dataset
dataset_queries_test = load_dataset("FOR-sight-ai/ECSS-1.0", "queries", split="test")

Results

Model Name	nDCG@10
bm25	0.43
bge-large-en-v1.5	0.44
nomic-embed-multimodal-3b	0.59
colqwen2.5-v0.2	0.68

Citation

If you use this dataset in your research or work, please cite:

@misc{ecssbenchmark2025,
  title={ECSS RAG benchmark},
  author={Francois Lancelot and Nawal Ould Amer and Benjamin Fourreau and Catherine Kobus and Marion-Cécile Martin},
  primaryClass={cs.IR},
  year={2025},
}