Triple
T22577105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Price |
E544433
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Buckshot |
—
|
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: Buckshot | Statement: [Sean Price, associatedAct, Buckshot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buckshot Context triple: [Sean Price, associatedAct, Buckshot]
-
A.
Buckshot
chosen
Buckshot is an American rapper best known as the frontman of the influential hip-hop group Black Moon and co-founder of the Boot Camp Clik collective.
-
B.
Bullshot
Bullshot is a 1983 British comedy film that parodies 1930s adventure serials and detective stories, produced by HandMade Films.
-
C.
Shotgun
"Shotgun" is a 1955 American Western film starring Sterling Hayden as a lawman pursuing outlaws across rugged frontier territory.
-
D.
Shotgun
"Shotgun" is a work associated with the character Abby, likely a creative piece such as a song, story, or artwork featuring or created by her.
-
E.
Shotgun
"Shotgun" is a catchy, upbeat pop song by English singer-songwriter George Ezra that became one of his biggest international hits.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15fedbddc8190bc50458a76f5407d |
completed | April 29, 2026, 1:33 a.m. |
Created at: April 16, 2026, 8:53 p.m.