configs:
- config_name: default
data_files:
- split: train
path: qrels/train.jsonl
- split: dev
path: qrels/dev.jsonl
- split: test
path: qrels/test.jsonl
- config_name: corpus
data_files:
- split: corpus
path: corpus.jsonl
- config_name: queries
data_files:
- split: queries
path: queries.jsonl
Dataset Summary
NFCorpus-Fa is a Persian (Farsi) dataset designed for the Retrieval task, with a focus on medical and nutrition information retrieval. It is a translated version of the original English NFCorpus (NutritionFacts Corpus), used in the BEIR benchmark, and is part of the FaMTEB (Farsi Massive Text Embedding Benchmark) under the BEIR-Fa collection.
- Language(s): Persian (Farsi)
- Task(s): Retrieval (Medical Information Retrieval, Nutrition Information Retrieval)
- Source: Translated from the English NFCorpus using Google Translate
- Part of FaMTEB: Yes — part of the BEIR-Fa collection
Supported Tasks and Leaderboards
This dataset evaluates models' ability to retrieve relevant scientific and nutritional content from a specialized corpus (PubMed articles) in response to health-related user queries. Performance can be compared on the Persian MTEB Leaderboard (filter by language: Persian).
Construction
- Translated from the NFCorpus dataset using the Google Translate API
- Original English dataset was curated using NutritionFacts.org queries and PubMed article annotations
Translation quality was validated using:
- BM25 score comparisons
- LLM-based assessment (GEMBA-DA framework)
Data Splits
As reported in the FaMTEB paper (Table 5):
- Train: 114,208 samples
- Dev: 0 samples
- Test: 15,967 samples
Approximate total dataset size: 141k examples (user-provided figure)