clearai-dsh

项目详情摘要

English · 中文 Your research, grown into an ontology.** ClearAI is an **ontology discovery and exploration platform**, built on two core concepts: **Domain ontology** (what you get) — your project's own vocabulary, the knowledge entries established through the loop, and their graphs. At the end of a research session you hold a continuously growing knowledge structure, retrievable next round by concept. **Epistemic loop** (how you get it) — question → ontology (how the relevant quantities are measured and how they affect each other) → candidate hypotheses with their predictions → a test that could fail → evidence → bounded conclusion → grows into the ontology. Every edge is tested by evidence and independent evaluation. Other knowledge graphs pile up edges by extraction and assertion; here every edge has to be earned through the loop. Restart `dsh web`, then pick **ClearAI** in the preset picker at the top of a new session. That is the whole setup. Full install notes ↓ Left: the Epistemic Loop. Its emerald fact dot is also the first node of the domain ontology on the right. Right: the ontology graph — dark is a concept, light is a value form, emerald an instance; the instance carries two contradictory assertions — **the two readings are tinted amber**, marking that they do not agree. The system reports the conflict; retracting or keeping is a human decision.* What you get: a domain ontology A **domain ontology** that grows as you research: **Vocabulary** — the language your project speaks: concepts, predicates, value forms, units. Conventions themselves carry no truth value; sentences written with them do. **Established entries** — knowledge that passed the loop: each with its boundary, support level, and evidence chain. Each entry states its boundary explicitly, so it can