Triple
T23385904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Kruithof |
E593878
|
entity |
| Predicate | fameOrigin |
P112499
|
FINISHED |
| Object | appearance on The Voice of Holland |
—
|
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: appearance on The Voice of Holland | Statement: [Sophia Kruithof, fameOrigin, appearance on The Voice of Holland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fameOrigin Context triple: [Sophia Kruithof, fameOrigin, appearance on The Voice of Holland]
-
A.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
B.
fameStatus
Indicates the level or state of public recognition or renown associated with an entity.
-
C.
fameExtent
Indicates the degree or scope of how widely recognized or renowned an entity is.
-
D.
famePeak
Indicates the time or point at which an entity reaches its highest level of fame or public recognition.
-
E.
starMadeFamous
chosen
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.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a498286c8190abfa381649812cf0 |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:35 p.m.