Triple
T7289271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Everything |
E163949
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Bang Bang |
E359288
|
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: Bang Bang | Statement: [My Everything, notableSong, Bang Bang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bang Bang Context triple: [My Everything, notableSong, Bang Bang]
-
A.
Bang Bang
chosen
"Bang Bang" is a 2014 pop/R&B hit single by Jessie J, Ariana Grande, and Nicki Minaj known for its powerful vocals and energetic, brass-driven production.
-
B.
Bang Bang
"Bang Bang" is a politically charged punk rock song by Green Day from their album "Revolution Radio."
-
C.
She Bangs
"She Bangs" is a 2000 Latin pop and dance hit by Ricky Martin known for its energetic rhythm, brassy production, and widespread international success.
-
D.
Bang Bang You're Dead
"Bang Bang You're Dead" is a 2002 American drama film that explores the psychological and social fallout of school violence through the story of a troubled high school student and his drama teacher.
-
E.
Boom Boom
"Boom Boom" is a classic 1961 electric blues song by John Lee Hooker that became one of his most famous and frequently covered recordings.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb6bde448190b52852c916a8059d |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eedfa4d08190997a692b81309309 |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3 p.m.