Triple
T14104905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Souled Out |
E339479
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Cocaine 80s |
E123231
|
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: Cocaine 80s | Statement: [Souled Out, featuresArtist, Cocaine 80s]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cocaine 80s Context triple: [Souled Out, featuresArtist, Cocaine 80s]
-
A.
Cocaine 80s
chosen
Cocaine 80s is a musical collective led by producer No I.D., known for its soulful, experimental R&B and hip-hop collaborations in the early 2010s.
-
B.
Cocaine Nights
Cocaine Nights is a dark, psychologically driven crime novel by J. G. Ballard that explores violence, boredom, and social control within an affluent expatriate community on the Costa del Sol.
-
C.
Cocaine (live)
"Cocaine (live)" is a live-performance track featured on The Internet's debut album "Purple Naked Ladies."
-
D.
Cocaine Bear
Cocaine Bear is a 2023 dark comedy horror film loosely inspired by the true story of a black bear that ingested a large amount of lost cocaine in a Georgia forest.
-
E.
Dopesick
Dopesick is a drama miniseries that explores the origins and devastating impact of the U.S. opioid crisis, focusing on the roles of pharmaceutical companies, doctors, and law enforcement.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbd02888190bf07fd6d8769b61c |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0b48e448190b4fb8cb33e5d97e6 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.