Triple
T1645608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South African general election, 1994 |
E35574
|
entity |
| Predicate | turnout |
P29796
|
FINISHED |
| Object | over 19 million voters |
—
|
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: over 19 million voters | Statement: [South African general election, 1994, turnout, over 19 million voters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnout Context triple: [South African general election, 1994, turnout, over 19 million voters]
-
A.
turns
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
B.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
C.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
D.
voterTurnoutPercentage
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
E.
turnedPro
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
- F. None of above. chosen
Provenance (4 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a9192f975c8190bfd514a4b5a8786c |
completed | March 5, 2026, 5:48 a.m. |
Created at: March 4, 2026, 7:28 p.m.