Triple
T76528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American time zones |
E1528
|
entity |
| Predicate | usesOffsetFrom |
P4824
|
FINISHED |
| Object | UTC |
—
|
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: UTC | Statement: [North American time zones, usesOffsetFrom, UTC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesOffsetFrom Context triple: [North American time zones, usesOffsetFrom, UTC]
-
A.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
-
B.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
C.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
D.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a25597b6c48190849c3e9e6351b983 |
completed | Feb. 28, 2026, 2:40 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.