Triple
T35122772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemi Eberechi Alade |
E1014205
|
entity |
| Predicate | gainedContinentalFameWith |
P57277
|
FINISHED |
| Object | Johnny |
—
|
NE NERFINISHED |
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: Johnny | Statement: [Yemi Eberechi Alade, gainedContinentalFameWith, Johnny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gainedContinentalFameWith Context triple: [Yemi Eberechi Alade, gainedContinentalFameWith, Johnny]
-
A.
madeInternationallyFamousBy
Indicates that one entity became widely known across multiple countries as a result of the actions, influence, or association of another entity.
-
B.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
C.
gainedProminenceAs
Indicates that an entity became widely recognized or notable in the role, capacity, or identity specified by another entity.
-
D.
starMadeFamous
Indicates that one entity (such as a work, event, or role) is what caused another entity (typically a person) to become widely known or famous.
-
E.
helpedPropelToMainstreamFame
chosen
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:01 p.m.