Triple
T31080534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LLL algorithm |
E792082
|
entity |
| Predicate | approximationGuarantee |
P145842
|
FINISHED |
| Object | produces basis with reasonably short vectors |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: produces basis with reasonably short vectors | Statement: [LLL algorithm, approximationGuarantee, produces basis with reasonably short vectors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximationGuarantee Context triple: [LLL algorithm, approximationGuarantee, produces basis with reasonably short vectors]
-
A.
hasApproximationGuarantee
chosen
Indicates that there exists a formal bound on how close a solution or outcome is to the optimal one.
-
B.
hasApproximationRatio
Indicates that there exists a quantitative bound describing how closely an algorithm’s solution approximates the optimal solution for a given problem.
-
C.
approximability
Indicates that one entity can be closely estimated, represented, or approached in value, form, or behavior by another, typically within some defined margin of error.
-
D.
approximationClass
Indicates a relationship where one entity is classified as an approximation or approximate representation of another.
-
E.
hasRandomizedApproximation
Indicates that there exists a randomized algorithm or method that can approximate the result of the referenced entity or process within some probabilistic accuracy or error bounds.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224ccdbbc81909b0cdb4cc2d70c7a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe2f078c24819082ba396b56f02808 |
completed | May 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69fe228fe1988190baf3bb34897f3dbe |
completed | May 8, 2026, 5:51 p.m. |
Created at: April 29, 2026, 9:02 p.m.