Triple
T27932311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South African general election, 1981 |
E708014
|
entity |
| Predicate | mainIssueContext |
P57423
|
FINISHED |
| Object | apartheid policy |
—
|
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: apartheid policy | Statement: [South African general election, 1981, mainIssueContext, apartheid policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainIssueContext Context triple: [South African general election, 1981, mainIssueContext, apartheid policy]
-
A.
majorContext
Indicates that one entity serves as the primary or most significant contextual framework within which the other entity is understood or interpreted.
-
B.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
C.
mainTitleIssues
Indicates that there are problems or concerns specifically related to the main title of an item, work, or record.
-
D.
primaryIssue
chosen
Indicates that the related item is the main or most important issue among a set of issues.
-
E.
modernIssue
Indicates that the subject is a contemporary or current-day issue affecting the object or broader 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 7:03 p.m.