Triple
T1040425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazakh language |
E22456
|
entity |
| Predicate | scriptChangePolicy |
P23827
|
FINISHED |
| Object | transition from Cyrillic to Latin alphabet in Kazakhstan |
—
|
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: transition from Cyrillic to Latin alphabet in Kazakhstan | Statement: [Kazakh language, scriptChangePolicy, transition from Cyrillic to Latin alphabet in Kazakhstan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptChangePolicy Context triple: [Kazakh language, scriptChangePolicy, transition from Cyrillic to Latin alphabet in Kazakhstan]
-
A.
changePolicy
Indicates that an entity modifies, replaces, or updates an existing policy governing rules, procedures, or behaviors.
-
B.
policyShift
Indicates a change or adjustment in an existing policy, typically reflecting a new direction, priority, or approach.
-
C.
implementedPolicy
Indicates that a particular policy has been put into effect or carried out by an entity.
-
D.
scriptAfterReform
Indicates that one script or writing system is used after a reform or modification has been applied to another script.
-
E.
replacedPolicyApproach
Indicates that one policy approach has been superseded and taken the place of another policy approach.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b845fa8c8190a7b69629883b62e2 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8444f708190815732408aa0463e |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:41 p.m.