structure-of-complaint

To extract structured data from a user review, you can convert the verbatim text into a JSON complaint graph. This process identifies specific pain points and expectations, outputting a network of typed nodes and edges for downstream analysis.

A complaint graph is a structured JSON representation of a user review that maps typed relationships between core issues. It uses five node types, such as lost value and triggered element, connected by four relation types to trace exactly how a problem impacts the user.

You turn verbatim quotes into a typed JSON graph by processing a review payload enclosed in user review tags. The system automatically anchors 3 to 7 generated nodes directly to the exact text from the review, ensuring complete traceability and data extraction accuracy.

Yes, the complaint graph extraction outputs a standardized JSON object containing nodes and edges, which is suitable for downstream audits and clustering. By mapping typed relations across multiple reviews, you can systematically analyze aggregated user pain and lost value.

The primary limitation is that the graph extraction operates on a single user review payload at a time rather than batch processing. Additionally, the output is strictly constrained to 3 to 7 nodes and four typed relations, which may oversimplify highly complex user feedback.