Triple
T35262477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Largo Prior do Crato |
E1018404
|
entity |
| Predicate | hasTypeOfBuildingAround |
P124983
|
FINISHED |
| Object | civic 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: civic buildings | Statement: [Largo Prior do Crato, hasTypeOfBuildingAround, civic buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfBuildingAround Context triple: [Largo Prior do Crato, hasTypeOfBuildingAround, civic buildings]
-
A.
hasNeighboringBuilding
Indicates that one building is located adjacent to or directly next to another building.
-
B.
hasNearbyInfrastructureType
chosen
Indicates that an entity is located close to infrastructure of a specified type.
-
C.
buildingTypeAtCenter
Indicates that a specific type of building is located at the central position of a given area or spatial context.
-
D.
hasMainBuildingNear
Indicates that the primary or central building associated with an entity is located in close physical proximity to another specified entity or place.
-
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_69f76de4be5c8190a51705c07612cac8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: May 3, 2026, 4:02 p.m.