Triple
T10717836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanity (outro) |
E252726
|
entity |
| Predicate | usesPersona |
P61233
|
FINISHED |
| Object | futuristic pop persona of Christina Aguilera |
—
|
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: futuristic pop persona of Christina Aguilera | Statement: [Vanity (outro), usesPersona, futuristic pop persona of Christina Aguilera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPersona Context triple: [Vanity (outro), usesPersona, futuristic pop persona of Christina Aguilera]
-
A.
hasPersona
chosen
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
B.
usedByPerson
Indicates that something (such as an object, tool, or resource) is utilized or employed by a person.
-
C.
usesProfile
Indicates that one entity employs, operates under, or is associated with a particular profile in performing its actions or functions.
-
D.
usesCharacter
Indicates that one entity employs, incorporates, or relies on a particular character (such as a symbol, letter, or persona) in its form, function, or representation.
-
E.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6ff36558c81908682adbe7b5dce05 |
completed | April 9, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69d6f30455888190b77f476b8418eaee |
completed | April 9, 2026, 12:29 a.m. |
Created at: April 8, 2026, 9:13 p.m.