Triple
T13476319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Majene |
E318260
|
entity |
| Predicate | hasAdministrativeBuildings |
P95689
|
FINISHED |
| Object | regency government offices |
—
|
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: regency government offices | Statement: [Majene, hasAdministrativeBuildings, regency government offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdministrativeBuildings Context triple: [Majene, hasAdministrativeBuildings, regency government offices]
-
A.
hasMunicipalBuildings
chosen
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
-
B.
hasTerminalBuildings
Indicates that one entity possesses or includes terminal buildings associated with it.
-
C.
hasNearbyCivicBuilding
Indicates that one entity is located close to, or in the immediate vicinity of, a civic building such as a government, public service, or community facility.
-
D.
hasOfficeBuildings
Indicates that one entity possesses, controls, or is associated with one or more office buildings.
-
E.
hasMultipleBuildings
Indicates that an entity possesses, controls, or is associated with more than one distinct building.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2551b48190a074fd256791742d |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.