Triple
T23046230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orb |
E573883
|
entity |
| Predicate | uniquenessBasis |
P36583
|
FINISHED |
| Object | uniqueness of human iris patterns |
—
|
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: uniqueness of human iris patterns | Statement: [Orb, uniquenessBasis, uniqueness of human iris patterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniquenessBasis Context triple: [Orb, uniquenessBasis, uniqueness of human iris patterns]
-
A.
uniquenessUpTo
Indicates that two entities are considered essentially the same because they differ, at most, by a specified equivalence or transformation.
-
B.
hasBasisIn
Indicates that one entity is founded, derived, or justified on the grounds of another entity.
-
C.
typeOfUniqueness
Indicates that one entity’s uniqueness is characterized, classified, or constrained by the specific kind or mode of uniqueness associated with another entity.
-
D.
identityBasis
chosen
Indicates that one entity serves as the defining basis, criterion, or foundation for determining the identity of another entity.
-
E.
hasCanonicalBasis
Indicates that there exists a standard or preferred basis associated with an entity, typically used as the reference basis in its context.
- 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_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f185192754819093a87d23371e7bbc |
completed | April 29, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
Created at: April 17, 2026, 3:54 p.m.