Triple
T146924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Apprentice |
E3349
|
entity |
| Predicate | prize |
P107
|
FINISHED |
| Object | job with a high-profile executive |
—
|
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: job with a high-profile executive | Statement: [The Apprentice, prize, job with a high-profile executive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prize Context triple: [The Apprentice, prize, job with a high-profile executive]
-
A.
prizeType
Indicates the specific category or kind of prize associated with an entity or event.
-
B.
awardFor
chosen
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
C.
awardType
Indicates the specific category or kind of award associated with an entity or event.
-
D.
awardReceived
Indicates that an entity has been granted or honored with a specific award or recognition.
-
E.
trophy
Indicates that one entity is a trophy awarded or possessed in relation to another entity, typically as a result of winning or achieving something.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.