--- license: apache-2.0 task_categories: - information-retrieval - text-retrieval tags: - beir - arguana - information-retrieval - retrieval - search configs: - config_name: corpus data_files: - split: train path: corpus/train-* - config_name: queries data_files: - split: train path: queries/train-* dataset_info: - config_name: corpus features: - name: metadata dtype: 'null' - name: text dtype: string - name: title dtype: string - name: _id dtype: string splits: - name: train num_bytes: 9388094 num_examples: 8674 download_size: 5024753 dataset_size: 9388094 - config_name: queries features: - name: metadata dtype: 'null' - name: text dtype: string - name: _id dtype: string splits: - name: train num_bytes: 1743698 num_examples: 1406 download_size: 949626 dataset_size: 1743698 --- # BEIR ARGUANA Dataset (Migrated) This is a migrated version of BeIR/arguana that is compatible with datasets library 4.0.0+. ## Dataset Description This dataset contains the arguana dataset from the BEIR benchmark, converted from the old script-based format to Parquet format. ## Dataset Structure ### Queries - **Split 'queries'**: 1,406 examples - Features: ['_id', 'text', 'metadata'] - **Total examples**: 1,406 ### Corpus - **Split 'corpus'**: 8,674 examples - Features: ['_id', 'title', 'text', 'metadata'] - **Total examples**: 8,674 ## Usage ```python from datasets import load_dataset # Load queries (split: queries) queries = load_dataset("Hyukkyu/beir-arguana", "queries", split="queries") # Load corpus (split: corpus) corpus = load_dataset("Hyukkyu/beir-arguana", "corpus", split="corpus") ``` ## Available Splits ### Queries - `queries`: 1,406 examples ### Corpus - `corpus`: 8,674 examples ## Original Dataset This dataset is migrated from: BeIR/arguana ## Citation If you use this dataset, please cite the original BEIR paper: ```bibtex @article{thakur2021beir, title={BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models}, author={Thakur, Nandan and Reimers, Nils and Ruckle, Andreas and Srivastava, Abhishek and Gurevych, Iryna}, journal={arXiv preprint arXiv:2104.08663}, year={2021} } ```