Triple
T20753906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bumiputera |
E510799
|
entity |
| Predicate | grantsBenefitType |
P75212
|
FINISHED |
| Object | educational quotas |
—
|
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: educational quotas | Statement: [Bumiputera, grantsBenefitType, educational quotas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantsBenefitType Context triple: [Bumiputera, grantsBenefitType, educational quotas]
-
A.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
B.
hasBenefitType
chosen
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
C.
benefitsOrganizationType
Indicates that something provides an advantage, support, or positive impact specifically to a particular type or category of organization.
-
D.
benefitAdministered
Indicates that a benefit (such as aid, service, or entitlement) has been formally provided or delivered to an eligible recipient by an administering party.
-
E.
benefitsLevel
Indicates the degree or extent to which one entity gains advantages, support, or positive outcomes from another entity or action.
- 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.