Triple
T20614988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luhn algorithm variant |
E506542
|
entity |
| Predicate | notDesignedToDetect |
P114207
|
FINISHED |
| Object | all possible multi-digit errors |
—
|
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: all possible multi-digit errors | Statement: [Luhn algorithm variant, notDesignedToDetect, all possible multi-digit errors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notDesignedToDetect Context triple: [Luhn algorithm variant, notDesignedToDetect, all possible multi-digit errors]
-
A.
notDesignedAs
chosen
Indicates that one entity was not created, intended, or purposed to serve as or function as the other entity.
-
B.
notObservedIn
Indicates that a particular entity, event, or property has not been detected, recorded, or seen within a specified context, dataset, or environment.
-
C.
notDescribedAs
Indicates that an entity is explicitly not characterized, labeled, or referred to using a particular description or term.
-
D.
notMeansTestedOn
Indicates that the benefit, service, or program is provided without assessing or depending on the recipient’s income or financial resources.
-
E.
notWellDocumented
Indicates that the subject lacks sufficient, clear, or comprehensive documentation.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aadaf47881909e93efb535c6c1e3 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.