Triple
T22247373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tina Snow |
E549879
|
entity |
| Predicate | embodiesPersona |
P68592
|
FINISHED |
| Object | confident rap persona |
—
|
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: confident rap persona | Statement: [Tina Snow, embodiesPersona, confident rap persona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: embodiesPersona Context triple: [Tina Snow, embodiesPersona, confident rap persona]
-
A.
roleOfCharacter
Indicates that one entity serves as the narrative or functional role played by a character within a story, scenario, or context.
-
B.
ultimatePersona
Indicates that one entity represents the final, most complete, or most authoritative persona or identity of another entity.
-
C.
playRoleIn
chosen
Indicates that an entity participates in or performs a specific function, character, or part within an event, context, or system.
-
D.
roleInCharacterBackstory
Indicates that one entity plays a specific role or part in shaping another entity’s character backstory or personal history.
-
E.
characterRoleSwap
Indicates a relationship where two characters exchange or assume each other’s narrative roles or functions within a story or scenario.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f13218d1f88190b64b7f301328fa98 |
completed | April 28, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
Created at: April 16, 2026, 8:38 p.m.