metadata
configs:
- config_name: default
data_files:
- 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
DBPedia-Fa is a Persian (Farsi) dataset tailored for the Retrieval task, focusing on entity retrieval. It is a translated version of the English DBpedia dataset used in the BEIR benchmark, and a key component of the FaMTEB (Farsi Massive Text Embedding Benchmark), under the BEIR-Fa collection.
- Language(s): Persian (Farsi)
- Task(s): Retrieval (Entity Retrieval)
- Source: Translated from the English DBpedia dataset used in BEIR
- Part of FaMTEB: Yes — under BEIR-Fa
Supported Tasks and Leaderboards
The dataset is used to evaluate text embedding models on their ability to retrieve structured entity information in response to heterogeneous queries. Results are benchmarked on the Persian MTEB Leaderboard on Hugging Face Spaces (language filter: Persian).
Construction
The dataset was created by:
- Translating an English DBpedia entity retrieval dataset into Persian using the Google Translate API
- Retaining the structure of the original knowledge base entity retrieval task, where the goal is to return accurate entities from DBpedia based on various query types
According to the FaMTEB paper, the BEIR-Fa datasets underwent:
- BM25 retrieval score comparisons with English counterparts
- LLM-based evaluation using the GEMBA-DA framework to confirm high translation quality for retrieval tasks
Data Splits
As reported in the FaMTEB paper (Table 5):
- Train: 0 samples
- Dev: 0 samples
- Test: 4,651,208 samples
Total: ~4.69 million examples