Triple
T33704832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakhytzhan Sagintayev |
E863557
|
entity |
| Predicate | officeStartTime (Akim of Almaty) |
P200387
|
FINISHED |
| Object | 2019-06-28 |
—
|
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: 2019-06-28 | Statement: [Bakhytzhan Sagintayev, officeStartTime (Akim of Almaty), 2019-06-28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeStartTime (Akim of Almaty) Context triple: [Bakhytzhan Sagintayev, officeStartTime (Akim of Almaty), 2019-06-28]
-
A.
officeStartTime (First Deputy Prime Minister of Kazakhstan)
Indicates the date and time when the individual began serving as First Deputy Prime Minister of Kazakhstan.
-
B.
officeStartTime (Governor of Kursk Oblast)
Indicates the time at which the Governor of Kursk Oblast officially begins their term in office.
-
C.
officeStartTime (Grand Vizier)
Indicates the time at which the Grand Vizier’s term in office officially begins.
-
D.
officeStartTime (Administrator of UNDP)
Indicates the date and time at which the person began serving as Administrator of UNDP.
-
E.
officeStartTime (Archivist of the United States)
Indicates the time at which the Archivist of the United States officially begins their term in office.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff878f41888190bcb3bc41ad26081a |
completed | May 9, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69ff854082d88190aad3bfedf05e849f |
completed | May 9, 2026, 7:04 p.m. |
| PDg | Predicate description generation | batch_69ff878e8334819097e3c4bb5ca6ffa5 |
completed | May 9, 2026, 7:14 p.m. |
Created at: May 1, 2026, 1:43 a.m.