Triple
T9131349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelsan Ellis as Bobby Byrd |
E219091
|
entity |
| Predicate | castingChoiceFor |
P87292
|
FINISHED |
| Object | supporting lead in Get on Up |
—
|
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: supporting lead in Get on Up | Statement: [Nelsan Ellis as Bobby Byrd, castingChoiceFor, supporting lead in Get on Up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: castingChoiceFor Context triple: [Nelsan Ellis as Bobby Byrd, castingChoiceFor, supporting lead in Get on Up]
-
A.
castIn
Indicates that an actor or performer appears in a particular film, show, or production.
-
B.
castingType
Indicates the specific method or category of casting used to transform or represent one entity in terms of another.
-
C.
castType
Indicates the specific kind or category of casting relationship that exists between two entities.
-
D.
castingReason
Indicates the reason or justification for selecting or assigning a particular entity (e.g., a person or object) to a specific role, function, or category.
-
E.
cast
Indicates that an agent selects and assigns a person or thing to play a specific role or function in a production or context.
- F. None of above. chosen
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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8ceea6c81909f368f12dac1649c |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:18 p.m.