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Description
InLegalNER is a dataset for training and evaluating Named Entity Recognition models on Indian court judgments. The dataset, created by opennyaiorg, defines 14 entity labels such as LAWYER, COURT, JUDGE, and STATUTE, which are mapped to components of a judgment like PREAMBLE and JUDGEMENT. It was last updated on Hugging Face on May 8, 2024.
Use Cases
Train NER models to identify legal professionals like LAWYER and JUDGE based on the defined label scheme.
Extract key case details such as CASE_NUMBER and DATE from judgment text.
Analyze the mention of legal entities like ORG and GPE within court documents.
Benchmark model performance on the specific 14-label taxonomy for Indian legal documents.
Strengths
Defines a specific 14-label taxonomy for Indian legal NER.
Entities are mapped to document components (PREAMBLE, JUDGEMENT), suggesting structured annotation.
Associated with a research paper titled 'Named Entity Recognition in Indian court judgments' on Arxiv.
Limitations
Row count, column definitions, and file formats are unknown, limiting suitability assessment.
Description metadata is limited; actual data quality requires manual inspection after download.
Last updated 2024-05-08 06:27:42; freshness should be verified.
Provenance
Source
opennyaiorg on Hugging Face
Collection Method
Likely annotated text from Indian court judgments.
Freshness
2024-05-08 06:27:42
Geography
India
License is unknown; terms of use must be verified before application.