Triple
T18131187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vsevolozhsky District |
E434013
|
entity |
| Predicate | hasUrbanTypeSettlements |
P115801
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Vsevolozhsky District, hasUrbanTypeSettlements, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanTypeSettlements Context triple: [Vsevolozhsky District, hasUrbanTypeSettlements, multiple]
-
A.
hasUrbanLocalities
chosen
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
-
B.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
-
C.
hasMajorSettlementsType
Indicates that an entity is associated with major settlements of a specified type (e.g., cities, towns, villages).
-
D.
hasCityStatusSettlement
Indicates that a settlement possesses official recognition or designation as a city.
-
E.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf1e2508190993f65ca137fdf63 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.