Triple
T37097157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vhavenda |
E918592
|
entity |
| Predicate | primaryCountryCitizenship |
—
|
GENERATED |
| Object | South African citizens |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCountryCitizenship Context triple: [Vhavenda, primaryCountryCitizenship, South African citizens]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
primaryNationality
chosen
Indicates the main national affiliation or citizenship that most strongly characterizes an entity among possibly multiple nationalities.
-
C.
nativeCountry
Indicates the country in which an entity (typically a person) was born or is originally from.
-
D.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, citizenship.
-
E.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
- F. None of above.
Provenance (1 batch)
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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:14 p.m.