Triple
T14037358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Angola |
E337746
|
entity |
| Predicate | hasOfficialVehicle |
P7735
|
FINISHED |
| Object | presidential motorcade of Angola |
—
|
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: presidential motorcade of Angola | Statement: [President of Angola, hasOfficialVehicle, presidential motorcade of Angola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialVehicle Context triple: [President of Angola, hasOfficialVehicle, presidential motorcade of Angola]
-
A.
hasVehicle
chosen
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
B.
hasVehicleAccess
Indicates that an entity is permitted to use or enter a particular vehicle.
-
C.
hasOfficial
Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
-
D.
hasPrimaryVehicularAccessTo
Indicates that one location or entity serves as the main route or means by which vehicles can reach or enter another location or entity.
-
E.
hasOfficialUse
Indicates that something is used in an authorized or formally recognized capacity, typically by an official body or for official purposes.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de30e312148190a6be0a3258364e6e |
completed | April 14, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.