Triple
T5895577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Merit Scholarship Corporation |
E131091
|
entity |
| Predicate | hasScholarshipType |
P2134
|
FINISHED |
| Object | one-time scholarships |
—
|
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: one-time scholarships | Statement: [National Merit Scholarship Corporation, hasScholarshipType, one-time scholarships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScholarshipType Context triple: [National Merit Scholarship Corporation, hasScholarshipType, one-time scholarships]
-
A.
hasScholarshipOn
Indicates that one entity provides or holds a scholarship related to another entity, such as a person receiving financial support for study at an institution or in a specific field.
-
B.
scholarshipType
chosen
Indicates the specific category or kind of scholarship associated with an entity.
-
C.
hasScholarships
Indicates that an entity provides, offers, or is associated with one or more scholarships to another entity.
-
D.
hasOrganScholarships
Indicates that an entity offers or provides scholarships specifically related to organ study or performance.
-
E.
hasBursaries
Indicates that an entity provides or is associated with bursaries (financial aid or scholarships).
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:58 p.m.