Triple
T14935597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École royale des élèves protégés |
E372382
|
entity |
| Predicate | studentSupport |
P116728
|
FINISHED |
| Object | financial assistance |
—
|
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: financial assistance | Statement: [École royale des élèves protégés, studentSupport, financial assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentSupport Context triple: [École royale des élèves protégés, studentSupport, financial assistance]
-
A.
academicSupport
Indicates that one entity provides educational assistance, guidance, or resources to help another entity succeed academically.
-
B.
studentsReceive
Indicates that one or more students are the recipients of something, such as instruction, resources, or communications, from another source.
-
C.
hasEducationalSupportFrom
Indicates that one entity receives educational assistance, guidance, or resources from another entity.
-
D.
studentComponent
Indicates that one entity functions as a student-related part, module, or subunit within a larger system, structure, or context.
-
E.
studentOrAssistant
Indicates that an individual has the role of either a student or an assistant in a given context or relationship.
- F. None of above. chosen
Provenance (4 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded647ae388190a0e97c03f2a4d832 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:37 a.m.