Triple
T22803024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosie the waitress |
E564450
|
entity |
| Predicate | createdForBrand |
P7551
|
FINISHED |
| Object | Bounty |
—
|
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: Bounty | Statement: [Rosie the waitress, createdForBrand, Bounty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bounty Context triple: [Rosie the waitress, createdForBrand, Bounty]
-
A.
Bounty
chosen
Bounty is a popular Procter & Gamble paper towel brand known for its high absorbency and durability.
-
B.
Bounty
Bounty is a chocolate bar brand consisting of coconut filling coated in milk or dark chocolate, produced and marketed by Mars, Incorporated.
-
C.
Bounty Killer
Bounty Killer is a Jamaican dancehall and reggae deejay known for his gritty delivery, influential 1990s hits, and role in shaping hardcore dancehall music.
-
D.
Bounty Trilogy
The Bounty Trilogy is a classic three-part historical novel series that dramatizes the famous mutiny on the HMS Bounty and its aftermath in the South Pacific.
-
E.
The Bounty Killer
The Bounty Killer is a Western novel by American author Marvin H. Albert, known for its gritty portrayal of frontier justice and professional manhunters in the Old West.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdf1e308190a05d0f61856be544 |
completed | April 29, 2026, 3:37 a.m. |
Created at: April 17, 2026, 3:31 p.m.