Triple
T6683878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miriam Makeba |
E152051
|
entity |
| Predicate | politicalCause |
P29201
|
FINISHED |
| Object | anti-apartheid movement |
—
|
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 movement | Statement: [Miriam Makeba, politicalCause, anti-apartheid movement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalCause Context triple: [Miriam Makeba, politicalCause, anti-apartheid movement]
-
A.
causeOfPoliticalConflict
Indicates that one entity is the source or reason for a political conflict involving another entity.
-
B.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
C.
politicalIssueFor
Indicates a relationship where a particular topic, problem, or policy area is considered a matter of political concern or debate for a given entity.
-
D.
politicalAct
chosen
Indicates that an entity performs, participates in, or is involved with an action related to politics, governance, or public policy.
-
E.
politicalGoal
Indicates a relationship where an entity aims to achieve, promote, or realize a specific political outcome, policy, or state of affairs.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.