Triple

T20122722
Position Surface form Disambiguated ID Type / Status
Subject Revolution Radio E490652 entity
Predicate single P3283 FINISHED
Object Bang Bang — 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: Bang Bang | Statement: [Revolution Radio, single, Bang Bang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bang Bang
Context triple: [Revolution Radio, single, Bang Bang]
  • A. Bang Bang
    "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 song by the American rock band ZZ Top, known for their blues-infused hard rock style.
  • C. Bang Bang
    "Bang Bang" is a popular song by the British electronic music duo Sweet Talker, known for its catchy hooks and dance-oriented production.
  • D. Bang Bang chosen
    "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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6673f5b4c8190bf9fb5f4e6b6a452 completed April 20, 2026, 5:49 p.m.
Created at: April 11, 2026, 11:30 p.m.