Triple
T22652884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smif-N-Wessun |
E559140
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Cocoa Brovaz |
—
|
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: Cocoa Brovaz | Statement: [Smif-N-Wessun, alsoKnownAs, Cocoa Brovaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cocoa Brovaz Context triple: [Smif-N-Wessun, alsoKnownAs, Cocoa Brovaz]
-
A.
Cocoa Brovaz
chosen
Cocoa Brovaz is a Brooklyn-based hip hop duo, formerly known as Smif-N-Wessun, recognized for their gritty lyricism and affiliation with the Boot Camp Clik collective.
-
B.
Cocoa
Cocoa is a small city on Florida’s Space Coast known for its historic downtown, proximity to Cape Canaveral, and role as a local educational hub.
-
C.
Cocoa
Cocoa is Apple’s native object-oriented application framework for building graphical user interfaces and other software on macOS.
-
D.
Cocoa
Cocoa is the dried and processed seed of the cacao tree, widely cultivated in tropical regions for use in chocolate, beverages, and various food products.
-
E.
Cocoa Hooves
Cocoa Hooves is a track from Glass Animals’ album *Zaba*, known for its hazy, psychedelic production and dreamy, tropical atmosphere.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1703d7d648190aafe275cd04c47cf |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:06 p.m.