Triple
T28996252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saemi Kim |
E736170
|
entity |
| Predicate | behindTheScenesRole |
P136019
|
FINISHED |
| Object | producer |
—
|
LITERAL 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: producer | Statement: [Saemi Kim, behindTheScenesRole, producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: behindTheScenesRole Context triple: [Saemi Kim, behindTheScenesRole, producer]
-
A.
roleInFilmProduction
chosen
Indicates the specific function or responsibility an entity has within the making of a film.
-
B.
roleInCinerama
Indicates that an entity has a role or participation in a Cinerama film or production.
-
C.
hasBehindTheScenesFilm
Indicates that one work includes or is associated with a behind-the-scenes film documenting its creation or production process.
-
D.
exploresBehindTheScenesOf
Indicates that an entity investigates and reveals the inner workings, hidden processes, or off-camera aspects of another entity.
-
E.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
- 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_69f077eacd0481908ef0bafd74491cd0 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fb599c08190aac2f24dda602f72 |
completed | May 2, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:31 a.m.