Triple
T24204216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attitude Adjustment |
E600058
|
entity |
| Predicate | associatedWithGimmick |
P155186
|
FINISHED |
| Object | John Cena’s main event 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: John Cena’s main event persona | Statement: [Attitude Adjustment, associatedWithGimmick, John Cena’s main event persona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithGimmick Context triple: [Attitude Adjustment, associatedWithGimmick, John Cena’s main event persona]
-
A.
associatedWithMonster
Indicates a relationship in which an entity is connected or linked in some notable way to a monster.
-
B.
associatedWithGame
Indicates that there is a relationship or connection between an entity and a particular game.
-
C.
associatedMystic
Indicates a relationship where one entity is linked or connected to another through a mystical, spiritual, or esoteric association.
-
D.
associatedWithGift
Indicates a relationship in which an entity is connected to, involved with, or linked through a gift.
-
E.
associatedDemon
Indicates that there exists a relationship in which one entity is linked or connected to a particular demon.
- F. None of above. chosen
Provenance (4 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27ca38c148190ae65cd692567d43d |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c9834064819082024233d9c6f98f |
completed | April 29, 2026, 9:04 a.m. |
Created at: April 17, 2026, 11:37 p.m.