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--- |
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language_creators: |
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- found |
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language: |
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- en |
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license: |
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- cc-by-nc-sa-4.0 |
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multilinguality: |
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- monolingual |
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pretty_name: eoir_privacy |
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source_datasets: [] |
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task_categories: |
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- text-classification |
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viewer: false |
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--- |
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# Dataset Card for eoir_privacy |
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## 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](#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-instances) |
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- [Data Splits](#data-instances) |
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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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## Dataset Description |
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- **Homepage:** [Needs More Information] |
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- **Repository:** [Needs More Information] |
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- **Paper:** [Needs More Information] |
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- **Leaderboard:** [Needs More Information] |
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- **Point of Contact:** [Needs More Information] |
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### Dataset Summary |
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This dataset mimics privacy standards for EOIR decisions. It is meant to help learn contextual data sanitization rules to anonymize potentially sensitive contexts in crawled language data. |
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### Languages |
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English |
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## Dataset Structure |
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### Data Instances |
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{ |
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"text" : masked paragraph, |
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"label" : whether to use a pseudonym in filling masks |
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} |
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### Data Splits |
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train 75%, validation 25% |
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## Dataset Creation |
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### Curation Rationale |
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This dataset mimics privacy standards for EOIR decisions. It is meant to help learn contextual data sanitization rules to anonymize potentially sensitive contexts in crawled language data. |
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### Source Data |
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#### Initial Data Collection and Normalization |
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We scrape EOIR. We then filter at the paragraph level and replace any references to respondent, applicant, or names with [MASK] tokens. We then determine if the case used a pseudonym or not. |
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#### Who are the source language producers? |
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U.S. Executive Office for Immigration Review |
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### Annotations |
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#### Annotation process |
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Annotations (i.e., pseudonymity decisions) were made by the EOIR court. We use regex to identify if a pseudonym was used to refer to the applicant/respondent. |
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#### Who are the annotators? |
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EOIR judges. |
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### Personal and Sensitive Information |
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There may be sensitive contexts involved, the courts already make a determination as to data filtering of sensitive data, but nonetheless there may be sensitive topics discussed. |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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This dataset is meant to learn contextual privacy rules to help filter private/sensitive data, but itself encodes biases of the courts from which the data came. We suggest that people look beyond this data for learning more contextual privacy rules. |
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### Discussion of Biases |
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Data may be biased due to its origin in U.S. immigration courts. |
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### Licensing Information |
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CC-BY-NC |
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### Citation Information |
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``` |
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@article{hendersonkrass2022pileoflaw, |
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title={Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset}, |
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author={Henderson*, Peter and Krass*, Mark and Zheng, Lucia and Guha, Neel and Manning, Christopher and Jurafsky, Dan and Ho, Daniel E}, |
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year={2022} |
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} |
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``` |