Triple
T37083910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Belle et la Bête (support to Jean Cocteau) |
E918230
|
entity |
| Predicate | associatedWithFairyTale |
—
|
GENERATED |
| Object | Beauty and the Beast |
—
|
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: associatedWithFairyTale Context triple: [La Belle et la Bête (support to Jean Cocteau), associatedWithFairyTale, Beauty and the Beast]
-
A.
associatedTale
chosen
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
B.
hasFairyCharacters
Indicates that the subject includes or features characters that are fairies.
-
C.
fictionalCharacterAssociatedWith
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
D.
folkloreCharacter
Indicates that one entity is a character originating from the traditional stories, myths, or legends associated with the other entity.
-
E.
associatedWithCaseInFiction
Indicates that an entity is connected to, involved in, or relevant to a particular case or investigation within a fictional context.
- 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_69f76e9952b88190a6fe01ba01476520 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:14 p.m.