arXiv (All)
open access
Schematize: An Agentic System for Generating and Refining Information-Extraction Schemas for Legal Research
Empirical legal research often relies on turning research questions into structured data extracted from large collections of rulings and judgments. Designing the extraction schema and then extracting the data remain a manual, expertise-heavy bottleneck. We present schematize, an open-source multi-ag
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A Semi-automated Ontology Construction for Legal Question Answering#679063
- An Ontological AI-and-Law Framework for the Autonomous Levels of AI Legal Reasoning#1178289
- Overview and Discussion of the Competition on Legal Information, Extraction/Entailment (COLIEE) 2023#679188
- Summary of the Competition on Legal Information, Extraction/Entailment (COLIEE) 2023#419010
- Multi-Granularity Argument Mining in Legal Texts#679224
Record · ID 1036892
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive