Triple
T5862591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver and Gold |
E130309
|
entity |
| Predicate | supportingCause |
P10437
|
FINISHED |
| Object | anti-apartheid activism |
—
|
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: anti-apartheid activism | Statement: [Silver and Gold, supportingCause, anti-apartheid activism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportingCause Context triple: [Silver and Gold, supportingCause, anti-apartheid activism]
-
A.
causeSupported
chosen
Indicates that an entity provides backing, endorsement, or assistance to a particular cause or initiative.
-
B.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
C.
helpedCause
Indicates that one entity contributed to bringing about, enabling, or facilitating an outcome or event involving another entity.
-
D.
benefitsCause
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or cause.
-
E.
sharesCauseWith
Indicates that two entities are associated with or arise from the same underlying cause or causal factor.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:56 p.m.