Triple
T267973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Standard Time |
E5773
|
entity |
| Predicate | regionSpan |
P4679
|
FINISHED |
| Object | about 5 geographical time zones |
—
|
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: about 5 geographical time zones | Statement: [China Standard Time, regionSpan, about 5 geographical time zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionSpan Context triple: [China Standard Time, regionSpan, about 5 geographical time zones]
-
A.
range
chosen
Indicates that a value, property, or effect extends between specified limits or over a specified interval or scope.
-
B.
peakTerritorialExtent
Indicates the maximum geographic area or territorial size that an entity controlled or occupied at the height of its expansion.
-
C.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
D.
spectralRegion
Indicates the portion of the electromagnetic spectrum (e.g., wavelength or frequency range) in which a measurement, observation, or property is defined or applies.
-
E.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.