Intent Accuracy
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Intent Accuracy has 5 facts recorded in Dontopedia across 3 references, with 1 live disagreement.
Maturity scale
raw canonical shape-checked rule-derived certifiedRdf:typein disputerdf:type
Improved byimprovedBy
- Llm Based Reformulation[1]all time · 14d0c405 2f52 4261 Ad38 13be7b76835d
Rdfs:labelrdfs:label
- Intent accuracy[1]all time · 14d0c405 2f52 4261 Ad38 13be7b76835d
Inbound mentions (7)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
accuracyMetricAccuracy Metric(1)
- Proof of Concept
ex:proof-of-concept
accuracyTypeAccuracy Type(1)
- Proof of Concept 91 Accuracy
ex:proof-of-concept-91-accuracy
appliesToApplies to(1)
- Observed Boost
ex:observed-boost
hasPerformanceMetricHas Performance Metric(1)
- Proof of Concept
ex:proof-of-concept
improvesImproves(1)
- Llm Based Reformulation
ex:llm-based-reformulation
measuresMeasures(1)
- 25 Percent Boost
ex:25-percent-boost
targetMetricTarget Metric(1)
- High Accuracy Goal
ex:high-accuracy-goal
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (3)
- custom
ctx:claims/beam/14d0c405-2f52-4261-ad38-13be7b76835d - custom
ctx:claims/beam/5d5ac388-fe7b-46be-8676-6c933e883590- full textbeam-chunktext/plain1 KB
doc:beam/5d5ac388-fe7b-46be-8676-6c933e883590Show excerpt
[Turn 10558] User: I'm conducting a POC to test LLM reformulation on 1,500 queries, and I'm hitting 91% intent accuracy. However, I'm not sure how to optimize my model for better performance. Can you help me explore different algorithms and…
- custom
ctx:claims/beam/63f3f6ff-b059-492e-954d-ccca67c2349d- full textbeam-chunktext/plain1020 B
doc:beam/63f3f6ff-b059-492e-954d-ccca67c2349dShow excerpt
However, I'm only achieving about 80% accuracy with this approach. I've studied LLM-based reformulation and noted a 25% intent accuracy boost for 6,000 complex queries. Can you help me improve my implementation to reach at least 92% detecti…
See also
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