UTokyo-Yokoya-Lab/webis-touche2020-v3-CSR-L

--- configs: - config_name: corpus data_files: - path: corpus/corpus-* split: corpus - config_name: default data_files: - path: data/test-* split: test - config_name: queries_zh_en data_files: - path: queries_zh_en/train-* split: train - config_name: queries_ja_en data_files: - path: queries_ja_en/train-* split: train dataset_info: - config_name: corpus features: - name: _id dtype: string - name: title dtype: string - name: text dtype: string splits: - name: corpus num_examples: 303732 - config_name: default features: - name: query-id dtype: string - name: corpus-id dtype: string - name: score dtype: float64 splits: - name: test num_examples: 2849 - config_name: queries_zh_en features: - name: _id dtype: string - name: text dtype: string - name: metadata struct: - name: description dtype: string - name: narrative dtype: string splits: - name: train num_examples: 49 - config_name: queries_ja_en features: - name: _id dtype: string - name: text dtype: string - name: metadata struct: - name: description dtype: string - name: narrative dtype: string splits: - name: train num_examples: 49 language: - eng - zho - jpn multilinguality: multilingual task_categories: - text-retrieval task_ids: [] tags: - mteb - text - code-switching --- <div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;"> <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">Touche2020-v3-CodeSwitching</h1> <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">An <a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;">MTEB</a> dataset</div> <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div> </div> Code-switching version of [mteb/webis-touche2020-v3](https://huggingface.co/datasets/mteb/webis-touche2020-v3), with queries rewritten in Chinese-English and Japanese-English code-switching styles. ## Dataset Structure The dataset contains the following configurations: **From original dataset (unchanged):** - `corpus`: Original corpus documents - `default`: Original relevance judgments (qrels) **Code-switching additions:** - `queries_zh_en`: Chinese-English code-switching queries - `queries_ja_en`: Japanese-English code-switching queries ## Usage ```python from datasets import load_dataset # Load code-switching queries queries_zh = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "queries_zh_en") queries_ja = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "queries_ja_en") # Load original configs corpus = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "corpus") qrels = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "default") ``` ## Attribution Based on [mteb/webis-touche2020-v3](https://huggingface.co/datasets/mteb/webis-touche2020-v3) (MIT License). ## Citation If you use this dataset, please also cite the original: ```bibtex @inproceedings{bondarenko2020overview, author = {Alexander Bondarenko and Maik Fr\"{o}be and Meriem Beloucif and Lukas Gienapp and Yamen Ajjour and Alexander Panchenko and Chris Biemann and Benno Stein and Henning Wachsmuth and Martin Potthast and Matthias Hagen}, booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. 11th International Conference of the CLEF Association (CLEF 2020)}, doi = {10.1007/978-3-030-58219-7\_26}, pages = {384--395}, title = {Overview of Touch\'{e} 2020: Argument Retrieval}, year = {2020}, } @article{enevoldsen2025mmtebmassivemultilingualtext, title={MMTEB: Massive Multilingual Text Embedding Benchmark}, author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and others}, journal={arXiv preprint arXiv:2502.13595}, year={2025}, url={https://arxiv.org/abs/2502.13595}, doi={10.48550/arXiv.2502.13595}, } @article{muennighoff2022mteb, author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo\"{\i}c and Reimers, Nils}, title = {MTEB: Massive Text Embedding Benchmark}, journal={arXiv preprint arXiv:2210.07316}, year = {2022}, url = {https://arxiv.org/abs/2210.07316}, doi = {10.48550/ARXIV.2210.07316}, } ```configs: - config_name: corpus data_files: - path: corpus/corpus-* split: corpus - config_name: default data_files: - path: data/test-* split: test - config_name: queries_zh_en data_files: - path: queries_zh_en/train-* split: train - config_name: queries_ja_en data_files: - path: queries_ja_en/train-* split: train dataset_info: - config_name: corpus features: - name: _id dtype: 字符串（string） - name: title dtype: 字符串（string） - name: text dtype: 字符串（string） splits: - name: corpus num_examples: 303732 - config_name: default features: - name: query-id dtype: 字符串（string） - name: corpus-id dtype: 字符串（string） - name: score dtype: 64位浮点数（float64） splits: - name: test num_examples: 2849 - config_name: queries_zh_en features: - name: _id dtype: 字符串（string） - name: text dtype: 字符串（string） - name: metadata struct: - name: description dtype: 字符串（string） - name: narrative dtype: 字符串（string） splits: - name: train num_examples: 49 - config_name: queries_ja_en features: - name: _id dtype: 字符串（string） - name: text dtype: 字符串（string） - name: metadata struct: - name: description dtype: 字符串（string） - name: narrative dtype: 字符串（string） splits: - name: train num_examples: 49 language: - 英语（eng） - 中文（zho） - 日语（jpn） multilinguality: 多语言 task_categories: - 文本检索（text-retrieval） task_ids: [] tags: - mteb - 文本 - 代码转换（code-switching） <div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;"> <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">Touche2020-v3-CodeSwitching</h1> <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">一款<a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;">大规模文本嵌入基准（Massive Text Embedding Benchmark，MTEB）</a>数据集</div> <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div> </div> 本数据集是[mteb/webis-touche2020-v3](https://huggingface.co/datasets/mteb/webis-touche2020-v3)的代码转换版本，其中查询语句被改写为中英混合与日英混合的代码转换格式。 ## 数据集结构 本数据集包含以下配置项： **源自原始数据集（未作修改）：** - `corpus`：原始语料库文档 - `default`：原始相关性判断文件（qrels） **代码转换新增配置：** - `queries_zh_en`：中英混合代码转换查询语句 - `queries_ja_en`：日英混合代码转换查询语句 ## 使用方法 python from datasets import load_dataset # 加载代码转换查询语句 queries_zh = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "queries_zh_en") queries_ja = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "queries_ja_en") # 加载原始配置项 corpus = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "corpus") qrels = load_dataset("UTokyo-Yokoya-Lab/webis-touche2020-v3-codeswitching", "default") ## 归属声明 本数据集基于[mteb/webis-touche2020-v3](https://huggingface.co/datasets/mteb/webis-touche2020-v3)构建，采用MIT许可协议。 ## 引用声明 若您使用本数据集，请同时引用以下原始文献： bibtex @inproceedings{bondarenko2020overview, author = {Alexander Bondarenko and Maik Fr"{o}be and Meriem Beloucif and Lukas Gienapp and Yamen Ajjour and Alexander Panchenko and Chris Biemann and Benno Stein and Henning Wachsmuth and Martin Potthast and Matthias Hagen}, booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. 11th International Conference of the CLEF Association (CLEF 2020)}, doi = {10.1007/978-3-030-58219-7_26}, pages = {384--395}, title = {Overview of Touché 2020: Argument Retrieval}, year = {2020}, } @article{enevoldsen2025mmtebmassivemultilingualtext, title={MMTEB: Massive Multilingual Text Embedding Benchmark}, author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and others}, journal={arXiv preprint arXiv:2502.13595}, year={2025}, url={https://arxiv.org/abs/2502.13595}, doi={10.48550/arXiv.2502.13595}, } @article{muennighoff2022mteb, author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo"{i}c and Reimers, Nils}, title = {MTEB: Massive Text Embedding Benchmark}, journal={arXiv preprint arXiv:2210.07316}, year = {2022}, url = {https://arxiv.org/abs/2210.07316}, doi = {10.48550/ARXIV.2210.07316}, }