Triple
T34967613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Low |
E1008444
|
entity |
| Predicate | characterPlayedByLucasBlack |
P200373
|
FINISHED |
| Object | Buddy Robinson |
—
|
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: Buddy Robinson | Statement: [Get Low, characterPlayedByLucasBlack, Buddy Robinson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedByLucasBlack Context triple: [Get Low, characterPlayedByLucasBlack, Buddy Robinson]
-
A.
characterPlayedBy Jonathan Tucker
Indicates that the specified character is portrayed or acted by Jonathan Tucker.
-
B.
characterPlayedByNicholasHamilton
Indicates that the subject is a character portrayed by the actor Nicholas Hamilton.
-
C.
characterPlayedBySamuelLJackson
Indicates that the subject is a character portrayed by the actor Samuel L. Jackson.
-
D.
characterPlayedByDickMiller
Indicates that the specified character is portrayed or acted by Dick Miller.
-
E.
worksForCharacterPlayedBy
Indicates that one character is employed by, or works under, another character who is portrayed by a specific actor.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff84df768c81908c65a1a7e33103ad |
completed | May 9, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69ff848d0af881908ee42c27a58af47e |
completed | May 9, 2026, 7:01 p.m. |
| PDg | Predicate description generation | batch_69ff84dec2848190b67a497d025c8880 |
completed | May 9, 2026, 7:02 p.m. |
Created at: May 3, 2026, 4 p.m.