IMLJP: Logic-Guided Multistage Inference for Explainable Judgment Prediction

SHerZH/IMLJP is a processed dataset used for research in explainable AI for legal judgment prediction. The current release is a small preview subset intended for visualizing data structure and format. A larger version may be released in the future after further cleaning, annotation checking, and privacy review.

Use Cases

• Training models for multidefendant judgment prediction based on legal case text.
• Developing logic-guided inference systems based on the described multistage framework.
• Researching explainable AI methods in the legal domain based on the dataset's annotations.

Strengths

• Dataset is specifically processed for research described in an academic paper.
• Data structure and format are available for preview and small-scale experiments.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

SHerZH

Collection Method

Processed for use in an academic paper.

Freshness

Last updated 2026-04-08 02:33:20; freshness should be verified.