Triple
T26966702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RP |
E679190
|
entity |
| Predicate | errorProbabilityBound |
P162835
|
FINISHED |
| Object | acceptance probability for yes-instances is at least 1/2 |
—
|
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: acceptance probability for yes-instances is at least 1/2 | Statement: [RP, errorProbabilityBound, acceptance probability for yes-instances is at least 1/2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorProbabilityBound Context triple: [RP, errorProbabilityBound, acceptance probability for yes-instances is at least 1/2]
-
A.
hasFailureProbability
Indicates that an entity is associated with a likelihood or chance that it will fail within a given context or conditions.
-
B.
boundedByApprox
Indicates that one quantity is constrained by another within an approximate or tolerance-based bound, rather than an exact strict limit.
-
C.
hasFailureProbabilitySymbol
Indicates that an entity is associated with a symbolic representation of its probability of failure.
-
D.
givesBoundOn
Indicates that one quantity provides an upper or lower limit (a bound) on the value or behavior of another quantity.
-
E.
hasApproximationGuarantee
Indicates that there exists a formal bound on how close a solution or outcome is to the optimal one.
- F. None of above. chosen
Provenance (4 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62e4168a48190b45268f922780da6 |
completed | May 2, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d5268ac8190835dc7119353b840 |
completed | May 2, 2026, 4:58 p.m. |
Created at: April 27, 2026, 6:36 a.m.