Triple
T23788484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | From Scratch (TV miniseries) |
E588022
|
entity |
| Predicate | hasSupportingActress |
P64757
|
FINISHED |
| Object | Anika Noni Rose |
—
|
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: Anika Noni Rose | Statement: [From Scratch (TV miniseries), hasSupportingActress, Anika Noni Rose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSupportingActress Context triple: [From Scratch (TV miniseries), hasSupportingActress, Anika Noni Rose]
-
A.
hasProminentSupportingActor
Indicates that an entity (such as a film or show) features a supporting actor whose role or recognition is notably significant within that work.
-
B.
supportingActressRole
chosen
Indicates that an actress performs a supporting (non-leading) role in a particular production or work.
-
C.
supportingActressNominee
Indicates that a person has been nominated for an award in the category of supporting actress.
-
D.
supportingActorOfWinningFilm
Indicates that an entity is a supporting actor in a film that has won a specified award or competition.
-
E.
supportingActorNominee
Indicates that an entity has been nominated for an award recognizing their performance in a supporting acting role.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c633f7908190bac7fdac5990920a |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:17 p.m.