Triple
T27867272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimirskaya Square |
E704388
|
entity |
| Predicate | hasBuildingTypeInSurroundings |
P50464
|
FINISHED |
| Object | residential buildings |
—
|
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: residential buildings | Statement: [Vladimirskaya Square, hasBuildingTypeInSurroundings, residential buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingTypeInSurroundings Context triple: [Vladimirskaya Square, hasBuildingTypeInSurroundings, residential buildings]
-
A.
hasNeighboringBuilding
Indicates that one building is located adjacent to or directly next to another building.
-
B.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified type.
-
C.
hasNearbyInfrastructureType
Indicates that an entity is located close to infrastructure of a specified type.
-
D.
hasBuildingStyleInSurroundings
Indicates that an entity is surrounded by or located in an area characterized by a particular building style.
-
E.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
- 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 27, 2026, 6:21 p.m.