Triple
T20753919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bumiputera |
E510799
|
entity |
| Predicate | contrastedWithCategory |
P11289
|
FINISHED |
| Object | non-Bumiputera |
—
|
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: non-Bumiputera | Statement: [Bumiputera, contrastedWithCategory, non-Bumiputera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastedWithCategory Context triple: [Bumiputera, contrastedWithCategory, non-Bumiputera]
-
A.
contrastedWithObject
Indicates that one entity is explicitly compared to another by highlighting their differences or opposing characteristics.
-
B.
oftenContrastedWith
chosen
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
C.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
D.
traditionalContrastWith
Indicates a relationship where one tradition, practice, or belief is explicitly set in opposition or difference to another, highlighting their contrasting characteristics.
-
E.
contrastedWithBoundary
Indicates a relationship where one entity is compared or set in opposition to a defining limit, edge, or boundary of another entity to highlight their differences.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c22d0ebc8190b17077326f540f98 |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:34 p.m.