Triple
T2260289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaspi |
E50021
|
entity |
| Predicate | administrativeRegionType |
P35772
|
FINISHED |
| Object | mkhare |
—
|
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: mkhare | Statement: [Kaspi, administrativeRegionType, mkhare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeRegionType Context triple: [Kaspi, administrativeRegionType, mkhare]
-
A.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
B.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
C.
usesAdministrativeDivisionType
chosen
Indicates that one entity employs or applies a particular type of administrative division as part of its territorial or organizational structure.
-
D.
countryOrRegion
Indicates that one entity is a country or geographic region associated with another entity (such as its location, jurisdiction, or area of relevance).
-
E.
hasAdministrativeArea
Indicates that one entity serves as the governing or jurisdictional area responsible for administering 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.