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--- |
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dataset_info: |
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- config_name: default |
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features: |
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- name: slug |
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dtype: string |
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- name: text_chunk |
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dtype: string |
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- name: embedding |
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sequence: float64 |
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splits: |
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- name: train |
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num_bytes: 17448677826 |
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num_examples: 3655376 |
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download_size: 14805980593 |
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dataset_size: 17448677826 |
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- config_name: small |
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features: |
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- name: slug |
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dtype: string |
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- name: text_chunk |
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dtype: string |
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- name: embedding |
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sequence: float32 |
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splits: |
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- name: train |
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num_bytes: 475656222.6698008 |
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num_examples: 99531 |
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- name: test |
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num_bytes: 23459991.330199156 |
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num_examples: 4909 |
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download_size: 488406448 |
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dataset_size: 499116214.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- config_name: small |
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data_files: |
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- split: train |
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path: small/train-* |
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- split: test |
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path: small/test-* |
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--- |
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# Dataset Card for "processed-old-with-embeddings" |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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Chunks of about 256 words split by whitespace and their embeddings computed with the pretrained spacy model ["de_dep_news_trf"] (https://github.com/explosion/spacy-models/releases/tag/de_dep_news_trf-3.6.1). |
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The splits are created with respect to sentence boundaries parsed with the same model, sentences are concatenated if the result does not exceed max_words = 256, therefore the chunk length varies. |
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### Supported Tasks and Leaderboards |
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[More Information Needed] |
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### Languages |
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This dataset contains texts from the legal domain in German language. (German court decisions) |
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## Dataset Structure |
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[More Information Needed] |
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### Data Instances |
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{'slug': 'ag-pinneberg-2003-12-19-68-ii-9302-weg', |
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'text_chunk': 'Die Berufung des Klägers gegen das am 23. April 2002 verkündete Urteil der 1. Zivilkammer des Landgerichts Wuppertal wird zurückgewiesen.\n\n Der Kläger trägt (...)', |
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'embedding': [-0.055155396461486816, -0.3904547095298767, -0.0033536632545292377, 0.8048776984214783, 0.30156993865966797, 0.5924882888793945, (...)]]} |
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### Data Fields |
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{ |
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'slug': data['slug'], |
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'text_chunk': text, |
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'embedding': embedding |
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} |
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### Data Splits |
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[More Information Needed] |
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## Dataset Creation |
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### Curation Rationale |
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[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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#### Who are the source language producers? |
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This dataset contains texts from the legal domain in German language. (German court decisions) |
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### Citation Information |
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@inproceedings{10.1145/3383583.3398616, |
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author = {Ostendorff, Malte and Blume, Till and Ostendorff, Saskia}, |
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title = {Towards an Open Platform for Legal Information}, |
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year = {2020}, |
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isbn = {9781450375856}, |
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publisher = {Association for Computing Machinery}, |
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address = {New York, NY, USA}, |
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url = {https://doi.org/10.1145/3383583.3398616}, |
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doi = {10.1145/3383583.3398616}, |
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booktitle = {Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020}, |
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pages = {385–388}, |
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numpages = {4}, |
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keywords = {open data, open source, legal information system, legal data}, |
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location = {Virtual Event, China}, |
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series = {JCDL '20} |
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} |
