Commercial Litigation Pleadings and Legal Documents Named Entity Recognition Dataset

#named entity recognition #legal entity extraction #entity classification #commercial litigation document analysis #legal entity identification #legal document review
  • 5000
  • 0.5GB
  • JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-10-19

AI Analysis & Value Prop

Designed for web-accessible commercial litigation complaints, answers, and related legal documents, this dataset provides source text, document types, and annotations for litigation-related entities. Coverage includes parties, counsel, courts, and businesses, contracts, and commercial products involved in disputes. The documents focus on claims and procedural narratives rather than judicial opinions, supporting task-specific fine-tuning, evaluation, and legal information extraction research.

Dataset Insights

Sample Examples

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Technical Specifications

FieldTypeDescription
file_namestringFile name
entitiesarrayLitigation-related named entities identified in the source text, with their text positions.
document_textstringOriginal text of the web-accessible legal document, used as input for entity recognition.
document_typestringDocument category identified from its content, such as a complaint, answer, or other legal document.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What types of legal documents are included?
The dataset focuses on commercial litigation and includes web-accessible complaints, answers, and other related legal documents, along with document-type information. The exact document types depend on the available samples and annotations.
Which entities are annotated?
Annotations focus on litigation-related named entities, including parties, counsel, courts, and businesses, contracts, and commercial products involved in disputes. Entity text positions support entity recognition and span extraction.
Which training and evaluation tasks does it support?
The dataset can support task-specific fine-tuning and evaluation of legal named entity recognition models, as well as legal information processing research. Because pleadings differ in language and structure from judicial opinions, validate model performance on the intended target task.
How can the data be obtained, and what should users check?
Obtain the data through channels provided by the dataset provider and confirm the applicable license, usage restrictions, and source requirements before use. Legal documents may contain sensitive or protected information, so conduct a compliance review before deployment or redistribution and follow applicable privacy and data protection rules.

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Cite this Work

@dataset{Mobiusi2026,
  title={Commercial Litigation Pleadings and Legal Documents Named Entity Recognition Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/cf1287d4bedaa10483f238d552f92603?dataset_task_cate_id=9},
  urldate={2026-10-17},
  keywords={commercial litigation dataset,legal document entity recognition,complaint data,answer pleading data,legal NLP,litigation entity annotation,legal text dataset,named entity recognition},
  version={1.0}
}

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