Triple
T22611084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China–Kazakhstan border |
E566701
|
entity |
| Predicate | timeZoneOnKazakhSide |
P148929
|
FINISHED |
| Object | UTC+5 |
—
|
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+5 | Statement: [China–Kazakhstan border, timeZoneOnKazakhSide, UTC+5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneOnKazakhSide Context triple: [China–Kazakhstan border, timeZoneOnKazakhSide, UTC+5]
-
A.
timeZoneOnRussianSide
Indicates that the referenced time zone is the one used on the Russian side of a border, region, or cross-border context.
-
B.
timeZoneOnAfghanSide
Indicates that the referenced time zone is the one used on the Afghan side of a border or boundary.
-
C.
timeZoneOnBelarusianSide
Indicates that the referenced time zone is the one used on the Belarusian side of a border, region, or context involving Belarus.
-
D.
timeZoneOnChineseSide
Indicates that the referenced time zone is the one used on the Chinese side of a border, boundary, or cross-border context.
-
E.
timeZonePakistanSide
Indicates that something is located in, follows, or is associated with the time zone used on the Pakistan side of a border or region.
- 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_69e245884860819081046ce07d5872c4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f167ea291c8190ba73ba678089f75d |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:56 p.m.