Triple
T17959831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johannesburg Indian High School |
E449048
|
entity |
| Predicate | segregatedUnder |
P127401
|
FINISHED |
| Object | apartheid education system |
—
|
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 education system | Statement: [Johannesburg Indian High School, segregatedUnder, apartheid education system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segregatedUnder Context triple: [Johannesburg Indian High School, segregatedUnder, apartheid education system]
-
A.
segregatedIn
chosen
Indicates that one entity is separated or isolated within a specific space, group, or context defined by another entity.
-
B.
segregatedFor
Indicates that one entity is separated or set apart from others specifically for the use, benefit, or association of another entity.
-
C.
segregatedRepresentation
Indicates that the representation of entities is separated into distinct groups or categories, rather than being combined or integrated.
-
D.
separatedIn
Indicates that two or more entities, once together or associated, have been divided, split, or otherwise placed into distinct parts, groups, or locations.
-
E.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b130b7a081908542a3bc6dab5842 |
completed | April 19, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.