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--- |
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annotations_creators: |
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- other |
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language_creators: |
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- found |
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language: |
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- bg |
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- cs |
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- da |
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- de |
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- el |
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- en |
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- es |
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- et |
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- fi |
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- fr |
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- ga |
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- hu |
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- it |
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- lt |
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- lv |
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- mt |
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- nl |
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- pl |
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- pt |
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- ro |
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- sk |
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- sl |
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- sv |
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license: |
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- cc-by-4.0 |
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multilinguality: |
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- multilingual |
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paperswithcode_id: null |
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pretty_name: "MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages" |
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size_categories: |
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- 10M<n<100M |
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source_datasets: |
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- original |
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task_categories: |
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- fill-mask |
|
|
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--- |
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|
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# Dataset Card for MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages |
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|
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## Table of Contents |
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|
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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|
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## Dataset Description |
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|
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- **Homepage:** |
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- **Repository:** [GitHub](https://github.com/JoelNiklaus/LegalDatasets/tree/main/pretrain/mc4_legal) |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** [Joel Niklaus](mailto:joel@niklaus.ai) |
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|
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### Dataset Summary |
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|
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This dataset contains large text resources (~106GB in total) from mc4 filtered for legal data that can be used for pretraining language models. |
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|
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This dataset uses a different filtering method compared to [mc4_legal](https://huggingface.co/datasets/joelito/mc4_legal) and uses the smaller filtered [c4](https://huggingface.co/datasets/c4) dataset for the English split to speed up the filtering. |
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|
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Use the dataset like this: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("joelito/mc4_legal", "de", split='train', streaming=True) |
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``` |
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|
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### Supported Tasks and Leaderboards |
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The dataset supports the task of masked language modeling. |
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|
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### Languages |
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The following languages are supported: bg, cs, da, de, el, en, es, et, fi, fr, ga, hu, it, lt, lv, mt, nl, pl, pt, ro, sk, sl, sv |
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|
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## Dataset Structure |
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|
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### Data Instances |
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The file format is jsonl.xz and there is a validation and train split available. |
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|
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### Data Fields |
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|
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[More Information Needed] |
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### Data Splits |
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#### Data Size |
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|
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```bash |
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$ xz --list data/*.xz |
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Strms Blocks Compressed Uncompressed Ratio Check Filename |
|
1 1 2,080.7 KiB 33.4 MiB 0.061 CRC64 data/bg.train.0.jsonl.xz |
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1 1 22.8 KiB 315.9 KiB 0.072 CRC64 data/bg.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,881.0 MiB 0.157 CRC64 data/cs.train.0.jsonl.xz |
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1 1 608.0 MiB 3,902.6 MiB 0.156 CRC64 data/cs.train.1.jsonl.xz |
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1 1 256.1 MiB 1,644.5 MiB 0.156 CRC64 data/cs.train.2.jsonl.xz |
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1 1 1,450.6 KiB 8,690.7 KiB 0.167 CRC64 data/cs.validation.0.jsonl.xz |
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1 1 7,578.6 KiB 38.3 MiB 0.193 CRC64 data/da.train.0.jsonl.xz |
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1 1 19.7 KiB 82.3 KiB 0.240 CRC64 data/da.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,026.9 MiB 0.201 CRC64 data/de.train.0.jsonl.xz |
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1 1 608.0 MiB 3,038.7 MiB 0.200 CRC64 data/de.train.1.jsonl.xz |
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1 1 608.0 MiB 3,036.1 MiB 0.200 CRC64 data/de.train.2.jsonl.xz |
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1 1 608.0 MiB 3,040.3 MiB 0.200 CRC64 data/de.train.3.jsonl.xz |
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1 1 608.0 MiB 3,038.6 MiB 0.200 CRC64 data/de.train.4.jsonl.xz |
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1 1 608.0 MiB 3,044.2 MiB 0.200 CRC64 data/de.train.5.jsonl.xz |
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1 1 608.0 MiB 3,043.8 MiB 0.200 CRC64 data/de.train.6.jsonl.xz |
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1 1 608.0 MiB 3,038.2 MiB 0.200 CRC64 data/de.train.7.jsonl.xz |
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1 1 55.1 MiB 274.7 MiB 0.201 CRC64 data/de.train.8.jsonl.xz |
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1 1 5,033.5 KiB 24.5 MiB 0.201 CRC64 data/de.validation.0.jsonl.xz |
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1 1 1,280.9 KiB 17.0 MiB 0.073 CRC64 data/el.train.0.jsonl.xz |
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1 1 5,552 B 15.7 KiB 0.346 CRC64 data/el.validation.0.jsonl.xz |
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1 1 608.0 MiB 2,602.1 MiB 0.234 CRC64 data/en.train.0.jsonl.xz |
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1 1 90.0 MiB 386.5 MiB 0.233 CRC64 data/en.train.1.jsonl.xz |
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1 1 826.6 KiB 3,298.8 KiB 0.251 CRC64 data/en.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,106.5 MiB 0.196 CRC64 data/es.train.0.jsonl.xz |
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1 1 608.0 MiB 3,118.1 MiB 0.195 CRC64 data/es.train.1.jsonl.xz |
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1 1 608.0 MiB 3,113.6 MiB 0.195 CRC64 data/es.train.2.jsonl.xz |
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1 1 608.0 MiB 3,122.5 MiB 0.195 CRC64 data/es.train.3.jsonl.xz |
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1 1 608.0 MiB 3,121.5 MiB 0.195 CRC64 data/es.train.4.jsonl.xz |
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1 1 608.0 MiB 3,122.9 MiB 0.195 CRC64 data/es.train.5.jsonl.xz |
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1 1 608.0 MiB 3,128.4 MiB 0.194 CRC64 data/es.train.6.jsonl.xz |
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1 1 608.0 MiB 3,129.5 MiB 0.194 CRC64 data/es.train.7.jsonl.xz |
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1 1 608.0 MiB 3,132.2 MiB 0.194 CRC64 data/es.train.8.jsonl.xz |
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1 1 528.5 MiB 2,722.5 MiB 0.194 CRC64 data/es.train.9.jsonl.xz |
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1 1 6,159.9 KiB 30.7 MiB 0.196 CRC64 data/es.validation.0.jsonl.xz |
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1 1 93.5 MiB 506.2 MiB 0.185 CRC64 data/et.train.0.jsonl.xz |
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1 1 136.2 KiB 571.3 KiB 0.238 CRC64 data/et.validation.0.jsonl.xz |
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1 1 60.6 MiB 312.6 MiB 0.194 CRC64 data/fi.train.0.jsonl.xz |
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1 1 63.2 KiB 262.4 KiB 0.241 CRC64 data/fi.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,400.7 MiB 0.179 CRC64 data/fr.train.0.jsonl.xz |
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1 1 608.0 MiB 3,405.5 MiB 0.179 CRC64 data/fr.train.1.jsonl.xz |
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1 1 135.9 MiB 763.7 MiB 0.178 CRC64 data/fr.train.2.jsonl.xz |
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1 1 1,414.3 KiB 7,626.1 KiB 0.185 CRC64 data/fr.validation.0.jsonl.xz |
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1 1 31.2 KiB 146.4 KiB 0.213 CRC64 data/ga.train.0.jsonl.xz |
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1 0 32 B 0 B --- CRC64 data/ga.validation.0.jsonl.xz |
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1 1 211.5 MiB 1,407.3 MiB 0.150 CRC64 data/hu.train.0.jsonl.xz |
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1 1 212.9 KiB 1,287.6 KiB 0.165 CRC64 data/hu.validation.0.jsonl.xz |
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1 1 608.0 MiB 2,963.4 MiB 0.205 CRC64 data/it.train.0.jsonl.xz |
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1 1 608.0 MiB 2,970.0 MiB 0.205 CRC64 data/it.train.1.jsonl.xz |
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1 1 608.0 MiB 2,973.7 MiB 0.204 CRC64 data/it.train.2.jsonl.xz |
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1 1 315.2 MiB 1,541.6 MiB 0.204 CRC64 data/it.train.3.jsonl.xz |
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1 1 2,419.3 KiB 11.2 MiB 0.211 CRC64 data/it.validation.0.jsonl.xz |
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1 1 9,966.7 KiB 38.2 MiB 0.255 CRC64 data/lt.train.0.jsonl.xz |
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1 1 17.2 KiB 84.7 KiB 0.203 CRC64 data/lt.validation.0.jsonl.xz |
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1 1 66.4 KiB 326.7 KiB 0.203 CRC64 data/lv.train.0.jsonl.xz |
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1 0 32 B 0 B --- CRC64 data/lv.validation.0.jsonl.xz |
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1 1 2,851.6 KiB 16.7 MiB 0.167 CRC64 data/mt.train.0.jsonl.xz |
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1 1 2,092 B 5,079 B 0.412 CRC64 data/mt.validation.0.jsonl.xz |
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1 1 14.6 MiB 71.6 MiB 0.203 CRC64 data/nl.train.0.jsonl.xz |
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1 1 23.5 KiB 79.2 KiB 0.296 CRC64 data/nl.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,635.5 MiB 0.167 CRC64 data/pl.train.0.jsonl.xz |
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1 1 608.0 MiB 3,646.0 MiB 0.167 CRC64 data/pl.train.1.jsonl.xz |
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1 1 401.9 MiB 2,409.0 MiB 0.167 CRC64 data/pl.train.2.jsonl.xz |
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1 1 1,870.5 KiB 10.5 MiB 0.173 CRC64 data/pl.validation.0.jsonl.xz |
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1 1 608.0 MiB 3,173.1 MiB 0.192 CRC64 data/pt.train.0.jsonl.xz |
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1 1 329.1 MiB 1,721.6 MiB 0.191 CRC64 data/pt.train.1.jsonl.xz |
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1 1 989.0 KiB 4,841.2 KiB 0.204 CRC64 data/pt.validation.0.jsonl.xz |
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1 1 365.2 MiB 2,237.9 MiB 0.163 CRC64 data/ro.train.0.jsonl.xz |
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1 1 419.2 KiB 2,320.4 KiB 0.181 CRC64 data/ro.validation.0.jsonl.xz |
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1 1 266.1 MiB 1,668.1 MiB 0.160 CRC64 data/sk.train.0.jsonl.xz |
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1 1 304.1 KiB 1,618.2 KiB 0.188 CRC64 data/sk.validation.0.jsonl.xz |
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1 1 81.6 MiB 416.1 MiB 0.196 CRC64 data/sl.train.0.jsonl.xz |
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1 1 101.0 KiB 416.6 KiB 0.242 CRC64 data/sl.validation.0.jsonl.xz |
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1 1 252.0 MiB 1,423.2 MiB 0.177 CRC64 data/sv.train.0.jsonl.xz |
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1 1 210.8 KiB 1,091.2 KiB 0.193 CRC64 data/sv.validation.0.jsonl.xz |
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------------------------------------------------------------------------------- |
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74 72 20.0 GiB 106.2 GiB 0.189 CRC64 74 files |
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``` |
|
|
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## Dataset Creation |
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|
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The dataset was created by filtering mc4 for legal data. |
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We used terms indicating legal citations to get the texts. |
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Note that this dataset can be quite noisy, and the quality is not known. |
|
|
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### Curation Rationale |
|
|
|
[More Information Needed] |
|
|
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### Source Data |
|
|
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#### Initial Data Collection and Normalization |
|
|
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[More Information Needed] |
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|
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#### Who are the source language producers? |
|
|
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[More Information Needed] |
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|
|
|
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### Annotations |
|
|
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#### Annotation process |
|
|
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[More Information Needed] |
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|
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#### Who are the annotators? |
|
|
|
[More Information Needed] |
|
|
|
### Personal and Sensitive Information |
|
|
|
[More Information Needed] |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed] |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed] |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed] |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
[More Information Needed] |
|
|
|
### Licensing Information |
|
|
|
[More Information Needed] |
|
|
|
### Citation Information |
|
|
|
[More Information Needed] |
|
|
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### Contributions |
|
|
|
Thanks to [@JoelNiklaus](https://github.com/joelniklaus) for adding this dataset. |
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|
