Triple
T7964435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crada |
E184961
|
entity |
| Predicate | notableWorkWith |
P26239
|
FINISHED |
| Object | Bun B |
E452148
|
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: Bun B | Statement: [Crada, notableWorkWith, Bun B]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bun B Context triple: [Crada, notableWorkWith, Bun B]
-
A.
Bun B
chosen
Bun B is an American rapper best known as one half of the influential Southern hip hop duo UGK and for his extensive solo work and guest appearances.
-
B.
Bun
Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
-
C.
BON
BON is the National Rail station code for Bolton railway station in Greater Manchester, England.
-
D.
Bum
Bum is the nickname of Bum Phillips, the colorful and beloved former NFL head coach best known for leading the Houston Oilers in the 1970s.
-
E.
Bung
Bung is an Indonesian honorific title commonly used to address men in a friendly, egalitarian, and nationalist context, especially prominent during the independence era.
- 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3ba0da588190853dda68bba0755a |
completed | March 31, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe093f00881909317eb4dd4fa1393 |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:12 p.m.