Triple
T22390702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricky Martin |
E553503
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | She Bangs |
—
|
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: She Bangs | Statement: [Ricky Martin, notableWork, She Bangs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: She Bangs Context triple: [Ricky Martin, notableWork, She Bangs]
-
A.
She Bangs
chosen
"She Bangs" is a 2000 Latin pop and dance hit by Ricky Martin known for its energetic rhythm, brassy production, and widespread international success.
-
B.
Gotta Bang
Gotta Bang is a component or section of the work "Manifesto," likely representing a distinct chapter, track, or segment within that larger creative project.
-
C.
Bang Bang Bang
"Bang Bang Bang" is a studio album by the American country-rock group Nitty Gritty Dirt Band, showcasing their blend of country, folk, and rock influences.
-
D.
Bang Bang
"Bang Bang" is a politically charged punk rock song by Green Day from their album "Revolution Radio."
-
E.
Bang Bang
Bang Bang is a 2014 Indian action-comedy film starring Hrithik Roshan and Katrina Kaif, known for its high-octane stunts and being an official remake of the Hollywood movie "Knight and Day."
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15859853c8190b849cb34a94106da |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.