Triple
T15653268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Busy Signal |
E376364
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Bounty Killer |
E376358
|
NE 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: Bounty Killer | Statement: [Busy Signal, associatedAct, Bounty Killer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bounty Killer Context triple: [Busy Signal, associatedAct, Bounty Killer]
-
A.
Bounty Killer
chosen
Bounty Killer is a Jamaican dancehall and reggae deejay known for his gritty delivery, influential 1990s hits, and role in shaping hardcore dancehall music.
-
B.
Bounty
Bounty is a popular Procter & Gamble paper towel brand known for its high absorbency and durability.
-
C.
The Bounty Hunter
The Bounty Hunter is a 2010 American action-comedy film starring Jennifer Aniston and Gerard Butler, centered on a bounty hunter tasked with capturing his ex-wife.
-
D.
The Bounty Hunter
The Bounty Hunter is a film featuring Bo Hopkins in a prominent role as a rugged lawman tracking fugitives.
-
E.
Kill V. Maim
"Kill V. Maim" is a high-energy, genre-blending electronic pop song by Grimes known for its aggressive vocals, futuristic production, and cult fan following.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef089948190902ec22f4d7bc932 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6797954c8190ac05ee3db634efa7 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:15 a.m.