Triple
T26392059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ika |
E663437
|
entity |
| Predicate | filmEditedByInWork |
P129656
|
FINISHED |
| Object | Noëlle Boisson |
—
|
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: Noëlle Boisson | Statement: [Ika, filmEditedByInWork, Noëlle Boisson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmEditedByInWork Context triple: [Ika, filmEditedByInWork, Noëlle Boisson]
-
A.
editedFilm
Indicates that one entity performed the film editing work on another entity, which is a film.
-
B.
editedFilmForDirector
Indicates that one person performed film editing work on a movie under the direction or supervision of a specific director.
-
C.
filmEditingNominee
Indicates that an entity was nominated for an award recognizing excellence in film editing for a particular film or work.
-
D.
filmEditing
chosen
Indicates that one entity is responsible for editing or assembling the footage of a film associated with another entity.
-
E.
filmEditingAcademyAward
Indicates that an entity received or is associated with an Academy Award specifically for film editing.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610c024f081908237794984538566 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 11:26 p.m.