Triple
T14487814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Ellen Cornish |
E359282
|
entity |
| Predicate | notableWork |
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: [Jessica Ellen Cornish, notableWork, Bang Bang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bang Bang Context triple: [Jessica Ellen Cornish, notableWork, Bang Bang]
-
A.
Bang Bang
"Bang Bang" is a politically charged punk rock song by Green Day from their album "Revolution Radio."
-
B.
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.
-
C.
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."
-
D.
Bang Bang
"Bang Bang" is a work associated with Stephen Bloom, likely a creative project such as a film, book, or television production in which he was significantly involved.
-
E.
Bang Bang
"Bang Bang" is a song by the American rock band ZZ Top, known for their blues-infused hard rock style.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930bd1d48190abd6c47da0a3ebc8 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d8f1bf081908c37f8f41767b382 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:20 a.m.