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Datasets:
HiTZ
/
critics_science_mt_benchmark

Tasks:
Translation
Text Generation
Modalities:
Text
Formats:
json
Languages:
English
Spanish
Basque
Size:
1K - 10K
Tags:
scientific-machine-translation
machine-translation
scientific-text
document-translation
multilingual
english
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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critics_science_mt_benchmark / docs /SCHEMA_SPECIFICATION.md
Rodrigo Agerri
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Canonical JSONL schema v1.1.0

One JSON object per source excerpt, one line per item. Full specification: schema/benchmark.schema.json (JSON Schema Draft 2020-12).

Primary key and grouping

  • id is the original, stable excerpt key, globally unique across batches. Duplicate IDs across batches are rejected even if the text matches.
  • batch_id identifies the originating input folder, batch_001 to batch_010; it is NOT a train/test split.
  • source.source_identifier retains the original source ID.
  • source.source_document_key is a provisional document grouping key derived from the source ID, not guaranteed to be an authoritative article identifier. source_document_key_status records this limitation.
  • source.article_doi, article_url, license, excerpt_location are nullable pending source verification; never populate these with guesses.
  • source.source_sha256 hashes the UTF-8 content of the exact English text (no normalization).

Translations

  • translations.es.mt and translations.eu.mt hold the exact machine translation and its supplied metadata. Do not alter or re-label the original generation model.
  • translations.es.post_edit and translations.eu.post_edit are null until real human post-edits exist. Never copy MT text into these fields as placeholder references.
  • A future post-edit object requires text, status (draft, reviewed, adjudicated), reviewed_date, reviewer_id (pseudonymous), revision; optional notes.

Evaluation-only flattening

The builder generates data/pairs/en-es/test.jsonl and data/pairs/en-eu/test.jsonl, with fields id, batch_id, topic, repository, source_document_key, source_text, source_sha256, target_lang, mt_text, reference_text, reference_status, mt_system, mt_prompt_version.

There is deliberately no training split and no fine-tuning export. Candidate MT and reference are separate fields, so evaluators can elect to distribute only input text and score submitted systems using withheld references.

Determinism and invariants

Builder rejects missing files, within-file duplicate IDs, misaligned language ID sets, missing source/target text, malformed translation metadata, duplicate IDs across all loaded batches, invalid schema records and unrecognized topics.

The schema cannot establish translation quality, article provenance or legal redistribution rights. Those remain manual-review requirements.

Optional human corrections are provided separately as post_edits/batch_NNN/es.json and eu.json using an array of records with id and fields required by the post-edit schema.

Storage paths

The canonical multilingual file is data/canonical/all_languages.jsonl. Generated per-batch canonical files are in data/canonical/batch_NNN.jsonl; the pair views are in data/pairs/ and batch validation output is in data/reports/. Raw input files stay unchanged in original_input/.