Triple
T5973294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesia Standard Time system |
E132925
|
entity |
| Predicate | numberOfOfficialTimeZones |
P24408
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Indonesia Standard Time system, numberOfOfficialTimeZones, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOfficialTimeZones Context triple: [Indonesia Standard Time system, numberOfOfficialTimeZones, 3]
-
A.
hasNumberOfNationalTimeZones
chosen
Indicates the quantity of distinct official time zones that a nation or country uses within its territory.
-
B.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
C.
numberOfTimeZonesCrossed
Indicates the count of distinct time zones that an entity passes through or traverses during a specified journey or process.
-
D.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
E.
offsetRangeOfTimeZones
Indicates that one entity specifies the span or limits of time zone offsets (e.g., from minimum to maximum UTC offsets) applicable to another entity.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:03 p.m.