Triple
T10280441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralteysky District |
E241084
|
entity |
| Predicate | hasUrbanDivision |
P50633
|
FINISHED |
| Object | municipal okrugs |
—
|
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: municipal okrugs | Statement: [Admiralteysky District, hasUrbanDivision, municipal okrugs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanDivision Context triple: [Admiralteysky District, hasUrbanDivision, municipal okrugs]
-
A.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
B.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
C.
dividesUrbanAreaInto
chosen
Indicates that one entity partitions or segments an urban area into distinct parts or zones.
-
D.
hasUrbanOkrug
Indicates that an entity is associated with, belongs to, or is administered as an urban okrug (a type of municipal urban district).
-
E.
hasUrbanDistrictFunction
Indicates that an entity serves the administrative or functional role of an urban district within a larger territorial or governance structure.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:38 a.m.