Triple
T27696712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2009 South African general election |
E698315
|
entity |
| Predicate | determinedOffice |
P151711
|
FINISHED |
| Object | President of South Africa |
—
|
NE NERFINISHED |
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: President of South Africa | Statement: [2009 South African general election, determinedOffice, President of South Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: determinedOffice Context triple: [2009 South African general election, determinedOffice, President of South Africa]
-
A.
controlledOffice
Indicates that one entity has authority over, manages, or directs the operations of a particular office or administrative location.
-
B.
identifiesOffice
Indicates that one entity serves to specify or recognize the particular office or official position associated with another entity.
-
C.
officeFounded
Indicates that an office or branch of an organization was established or created at a particular time or place.
-
D.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
E.
subjectOffice
chosen
Indicates the office or official position held by the subject in relation to another entity or context.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6359fecc081908e1794c1905c5cc4 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:54 p.m.