Triple
T20933426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyrillic script for Kazakh |
E515523
|
entity |
| Predicate | officiallyAdoptedInKazakhSSR |
P36255
|
FINISHED |
| Object | 1940 |
—
|
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: 1940 | Statement: [Cyrillic script for Kazakh, officiallyAdoptedInKazakhSSR, 1940]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officiallyAdoptedInKazakhSSR Context triple: [Cyrillic script for Kazakh, officiallyAdoptedInKazakhSSR, 1940]
-
A.
officiallyAdopted
chosen
Indicates that an entity has been formally accepted, approved, or enacted by an authorized body or process as the recognized standard or version.
-
B.
nameInKazakh
Indicates that an entity is referred to by a particular name in the Kazakh language.
-
C.
laterAdoptedIn
Indicates that one entity was adopted, implemented, or taken up in another entity at a subsequent time relative to some earlier reference point or context.
-
D.
dateRenamedToNurSultan
Indicates the date on which something (typically a place or entity) was renamed to "Nur-Sultan".
-
E.
rankByAreaInKazakhstan
Indicates the relative ordering of entities based on the size of their area within the geographic boundaries of Kazakhstan.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f94e980c819083280a9c35af5930 |
completed | April 21, 2026, 4:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:49 p.m.