Triple
T32645859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinocchio (2022 film) |
E834593
|
entity |
| Predicate | characterPortrayedByCynthiaErivo |
P1507
|
FINISHED |
| Object | Blue Fairy |
—
|
NE NERFINISHED |
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: Blue Fairy | Statement: [Pinocchio (2022 film), characterPortrayedByCynthiaErivo, Blue Fairy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPortrayedByCynthiaErivo Context triple: [Pinocchio (2022 film), characterPortrayedByCynthiaErivo, Blue Fairy]
-
A.
characterPortrayedByKarenBlack
Indicates that a given character is portrayed or played by the actress Karen Black.
-
B.
characterPortrayedBySandrineBonnaire
Indicates that a character is portrayed or played by the actress Sandrine Bonnaire.
-
C.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
D.
characterPlayedBy Emmanuelle Chriqui
Indicates that the role or character in question is portrayed or acted by Emmanuelle Chriqui.
-
E.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given work.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: May 1, 2026, 1:07 a.m.