Triple
T21941105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sobradinho |
E541820
|
entity |
| Predicate | hasProximityToNationalCapital |
P117282
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sobradinho, hasProximityToNationalCapital, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProximityToNationalCapital Context triple: [Sobradinho, hasProximityToNationalCapital, true]
-
A.
isNearCapitalCity
chosen
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
B.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
-
C.
adjacentToProvinceCapital
Indicates that a location is directly next to or bordering the capital city of a province.
-
D.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
E.
locatedInNationCapitalRegion
Indicates that an entity is situated within the capital region of a specific nation.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12422245c8190af128b29e2d9c1fc |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.