Triple
T29630199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikpeng |
E755550
|
entity |
| Predicate | hasEducationEfforts |
P2489
|
FINISHED |
| Object | bilingual education programs |
—
|
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: bilingual education programs | Statement: [Ikpeng, hasEducationEfforts, bilingual education programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationEfforts Context triple: [Ikpeng, hasEducationEfforts, bilingual education programs]
-
A.
hasEducationFund
Indicates that an entity possesses or is associated with a dedicated fund intended to support educational expenses or activities.
-
B.
hasEducationServices
Indicates that one entity provides or offers educational services to another entity or within a particular context.
-
C.
hasEducationalMission
Indicates that an entity is responsible for or engaged in carrying out an educational purpose, goal, or function.
-
D.
hasEducationalProgram
chosen
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
E.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
- 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_69f0ef88fbe081908f0ad90c1c413f1c |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 6:40 p.m.