Triple

T20122715
Position Surface form Disambiguated ID Type / Status
Subject Revolution Radio E490652 entity
Predicate hasPart P35 FINISHED
Object Bouncing Off the Wall 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: Bouncing Off the Wall | Statement: [Revolution Radio, hasPart, Bouncing Off the Wall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bouncing Off the Wall
Context triple: [Revolution Radio, hasPart, Bouncing Off the Wall]
  • A. Bouncing Off the Wall chosen
    "Bouncing Off the Wall" is a song by the American punk rock band Green Day from their album "Revolution Radio."
  • B. Bounce
    "Bounce" is a popular Afrobeats song by Nigerian singer Rema, known for its energetic production and catchy, dance-oriented style.
  • C. Bounce
    Bounce is a character associated with the "Woman of Steel" universe, likely serving as a dynamic, action-oriented counterpart or ally distinguished by agility and resilience.
  • D. Bounce
    "Bounce" is a song best known as a single by the artist Woman of Steel, accompanied by an official music video.
  • E. Bounce
    Bounce is a popular brand of fabric softener dryer sheets known for reducing static cling and adding fragrance to laundry.
  • 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.