Triple
T28147106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everage |
E714512
|
entity |
| Predicate | characterTypeAssociation |
P49696
|
FINISHED |
| Object | housewife-turned-megastar |
—
|
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: housewife-turned-megastar | Statement: [Everage, characterTypeAssociation, housewife-turned-megastar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeAssociation Context triple: [Everage, characterTypeAssociation, housewife-turned-megastar]
-
A.
relatedCharacterType
Indicates that one character has a specified type of relationship or role in connection to another character.
-
B.
helpsCharacterType
Indicates that one character type provides assistance or support to another character type.
-
C.
employsCharacterType
Indicates that an entity makes use of or features a particular type or category of character in its content or structure.
-
D.
associatedWithFilmCharacterType
Indicates that an entity has an association or connection with a particular type or category of film character.
-
E.
workCharacterType
chosen
Indicates that a work involves or features a character of a specified type or role.
- 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_69efd6b033208190bf74f80a147e2092 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 27, 2026, 9:57 p.m.