Query Reformulation Approach
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Query Reformulation Approach has 3 facts recorded in Dontopedia across 1 reference.
3 facts·3 predicates·1 sources
Maturity scale
raw canonical shape-checked rule-derived certifiedOther facts (3)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
3 facts
| Predicate | Value | Ref |
|---|---|---|
| Has Accuracy | 80 | [1] |
| Rdf:type | Llm Based Approach | [1] |
| Used for | Query Reformulation | [1] |
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.
—
hasAccuracybeam/63f3f6ff-b059-492e-954d-ccca67c2349d
80
—
typebeam/63f3f6ff-b059-492e-954d-ccca67c2349d
ex:LLM-based-approach
—
usedForbeam/63f3f6ff-b059-492e-954d-ccca67c2349d
ex:query-reformulation
References (1)
1 references
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
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.