Developed Extraction Pipeline and Legal Research Queries

• Day: 2026-02-23
• Time: 22:30 to 23:45
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Data Extraction, Legal Research, Knowledge Management, NLP, Political Strategy

Description

Session Goal

The session aimed to develop a structured approach for data extraction and legal research queries, focusing on candidate streams, knowledge management, political frameworks, and legal implications in various contexts.

Key Activities

• Data Extraction: Developed a workflow for extracting candidate streams, including concepts, claims, and playbook moves, with a focus on disciplined extraction to avoid vague topics and duplicates.
• Knowledge Management System: Proposed an architecture for a knowledge management system, differentiating between stable knowledge (wiki) and dynamic narrative (blog).
• Political Context Mapping: Created an outline for mapping semantic scope in political contexts, addressing governance and strategy.
• Annotation Design: Designed a production annotation operator for NLP mining, emphasizing high recall extraction, traceability, and quality control.
• Legal Research: Conducted legal research on vehicle owner liability, focusing on permissive use, vicarious liability, and negligent entrustment across various states, with specific attention to Florida statutes.

Achievements

• Established a clear framework for data extraction and annotation design.
• Developed comprehensive legal research queries for vehicle owner liability and Florida’s legal implications.

Pending Tasks

• Further development of the knowledge management system architecture.
• Detailed implementation of the political context mapping framework.

Evidence

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