Triple
T27130670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Klein Blue |
E681553
|
entity |
| Predicate | hexApproximation |
P4460
|
FINISHED |
| Object | #002FA7 |
—
|
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: #002FA7 | Statement: [International Klein Blue, hexApproximation, #002FA7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hexApproximation Context triple: [International Klein Blue, hexApproximation, #002FA7]
-
A.
representsApproximately
Indicates that one entity serves as an inexact or close-but-not-exact representation or value of another entity.
-
B.
approximates
chosen
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
C.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
D.
approximateSquare
Indicates that one quantity is approximately equal to the square of another quantity, within some acceptable margin of error.
-
E.
offsetStandardApprox
Indicates that one value serves as an approximate standard or baseline from which another value is offset or deviates.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624772f14819092ad0064e574523d |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 9:04 a.m.