Triple
T22071129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Lips |
E545407
|
entity |
| Predicate | hasBside |
P15273
|
FINISHED |
| Object | Roulette |
—
|
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: Roulette | Statement: [Sugar Lips, hasBside, Roulette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roulette Context triple: [Sugar Lips, hasBside, Roulette]
-
A.
Roulette
Roulette is a popular casino game of chance in which players bet on where a ball will land on a spinning numbered wheel.
-
B.
Roulette
chosen
"Roulette" is a song by the Red Hot Chili Peppers featured on their 2022 album *Return of the Dream Canteen*.
-
C.
Chinese Roulette
Chinese Roulette is a 1976 psychological drama film by Rainer Werner Fassbinder that explores cruelty, deception, and power dynamics within a wealthy German family.
-
D.
Roulette Farm
Roulette Farm is a historic farmstead on the Antietam National Battlefield in Maryland, notable for its role and location near the Sunken Road during the American Civil War.
-
E.
Baccarat
Baccarat is a renowned French luxury brand best known for its exquisite crystal glassware, chandeliers, and decorative objects.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128881af481909b28cda2d343f4e3 |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.