Triple
T35067993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady & Peebles |
E1011783
|
entity |
| Predicate | featuresRoyalCharacter |
—
|
GENERATED |
| Object | Princess Bubblegum |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRoyalCharacter Context triple: [Lady & Peebles, featuresRoyalCharacter, Princess Bubblegum]
-
A.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
B.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
C.
featuresPrincess
chosen
Indicates that something includes or prominently presents a princess as a central element or character.
-
D.
featuresReturningCharacterFrom
Indicates that a work includes the reappearance of a character who previously appeared in the referenced source work.
-
E.
featuresCharacterRescue
Indicates that a work includes a scene or storyline in which one character rescues or saves another.
- F. None of above.
Provenance (1 batch)
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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:01 p.m.