Triple
T8786000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biko |
E209043
|
entity |
| Predicate | helpedRaiseAwarenessOf |
P33868
|
FINISHED |
| Object | apartheid |
—
|
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 | Statement: [Biko, helpedRaiseAwarenessOf, apartheid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedRaiseAwarenessOf Context triple: [Biko, helpedRaiseAwarenessOf, apartheid]
-
A.
aimsToRaiseAwarenessOf
Indicates that an entity undertakes actions or efforts with the purpose of increasing others’ knowledge, concern, or recognition of a particular issue, topic, or situation.
-
B.
awareness
Indicates that an entity has conscious knowledge, perception, or understanding of another entity, situation, or fact.
-
C.
helpedCause
chosen
Indicates that one entity contributed to bringing about, enabling, or facilitating an outcome or event involving another entity.
-
D.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
E.
helpedShowcase
Indicates that one entity actively assisted in presenting, promoting, or displaying another entity to an audience.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f758d348190804942d985f2337c |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.