HotpotQA: Triplet Subset for Dense Retrieval Training

A reformatted subset of the HotpotQA dataset used to train the BGE-M3 dense retrieval model. The data consists of text triplets with anchor questions, positive passages, and negative passages. The dataset was created by the sentence-transformers organization and was last updated on Hugging Face in June 2024.

Use Cases

• Training dense passage retrievers based on the provided anchor-positive-negative triplet structure.
• Evaluating contrastive learning methods for question-answering tasks.
• Fine-tuning embedding models for improved semantic search performance.
• Benchmarking information retrieval systems on multi-hop reasoning data.

Strengths

• Contains structured triplets specifically formatted for training retrieval models.
• Derived from the established HotpotQA benchmark for multi-hop question answering.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent for the main dataset; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Hugging Face (sentence-transformers/hotpotqa), derived from the original HotpotQA dataset.

Collection Method

Reformatted for model training, likely involving passage extraction and negative sampling.

Freshness

Last updated 2024-06-18 21:01:51; freshness should be verified.