Triple
T37083910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Belle et la Bête (support to Jean Cocteau) |
E918230
|
entity |
| Predicate | associatedWithFairyTale |
P102058
|
FINISHED |
| Object | Beauty and the Beast |
E970208
|
NE 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: Beauty and the Beast | Statement: [La Belle et la Bête (support to Jean Cocteau), associatedWithFairyTale, Beauty and the Beast]
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 (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_69f76e9952b88190a6fe01ba01476520 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3efdc6b29481909666206a2ad378c1 |
completed | June 26, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.