Triple
T5771918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State President of South Africa |
E127349
|
entity |
| Predicate | officeHolderTitleInAfrikaans |
P3342
|
FINISHED |
| Object | Staatspresident van Suid-Afrika |
—
|
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: Staatspresident van Suid-Afrika | Statement: [State President of South Africa, officeHolderTitleInAfrikaans, Staatspresident van Suid-Afrika]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTitleInAfrikaans Context triple: [State President of South Africa, officeHolderTitleInAfrikaans, Staatspresident van Suid-Afrika]
-
A.
officeHolderTitle
chosen
Indicates the official position or title held by a person in an office or role.
-
B.
officeHolderTitleInPortuguese
Indicates the official title or designation of an office holder as expressed in the Portuguese language.
-
C.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
D.
officeHolderTitleInLatin
Indicates that the specified office holder’s title is expressed in its Latin-language form.
-
E.
headOfOffice
Indicates that one entity serves as the chief or leading authority in charge of a particular office or organizational unit.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.