Triple

T5864926
Position Surface form Disambiguated ID Type / Status
Subject Boomerang II E130366 entity
Predicate isFollowUpTo P134 FINISHED
Object Boomerang I
Boomerang I is the original work or installment that precedes and sets the foundation for its successor, Boomerang II.
 E557224 NE FINISHED

How this triple was built (4 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: Boomerang I | Statement: [Boomerang II, isFollowUpTo, Boomerang I]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Boomerang I
Context triple: [Boomerang II, isFollowUpTo, Boomerang I]
  • A. Boomerang II
    Boomerang II is a lesser-known track by Irish rock band U2, released as a B-side during their mid-1980s era.
  • B. Boomerang!
    Boomerang! is a 1947 American film noir crime drama noted for its semi-documentary style and exploration of a real-life wrongful murder accusation.
  • C. Boomerang
    Boomerang is a steel shuttle roller coaster known for its forward-and-backward looping layout, operating at the Worlds of Fun amusement park in Kansas City, Missouri.
  • D. Boomerang
    Boomerang is a television network known for airing classic and contemporary animated programming, particularly cartoons from the Warner Bros. and Hanna-Barbera libraries.
  • E. Boomerang
    Boomerang is a 1992 romantic comedy film starring Eddie Murphy that follows a suave advertising executive whose womanizing ways are challenged when he meets his match.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Boomerang I
Triple: [Boomerang II, isFollowUpTo, Boomerang I]
Generated description
Boomerang I is the original work or installment that precedes and sets the foundation for its successor, Boomerang II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Boomerang I
Target entity description: Boomerang I is the original work or installment that precedes and sets the foundation for its successor, Boomerang II.
  • A. Boomerang II
    Boomerang II is a lesser-known track by Irish rock band U2, released as a B-side during their mid-1980s era.
  • B. Boomerang!
    Boomerang! is a 1947 American film noir crime drama noted for its semi-documentary style and exploration of a real-life wrongful murder accusation.
  • C. Boomerang
    Boomerang is a steel shuttle roller coaster known for its forward-and-backward looping layout, operating at the Worlds of Fun amusement park in Kansas City, Missouri.
  • D. Boomerang
    Boomerang is a television network known for airing classic and contemporary animated programming, particularly cartoons from the Warner Bros. and Hanna-Barbera libraries.
  • E. Boomerang
    Boomerang is a 1992 romantic comedy film starring Eddie Murphy that follows a suave advertising executive whose womanizing ways are challenged when he meets his match.
  • F. None of above. chosen

Provenance (5 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_69c0084f3bb08190a7720f55f7aa4252 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035bfa8188190ab0e28101fdf5e6f completed March 22, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bfdd5920819087f48db024e4a3ed completed March 23, 2026, 4:21 a.m.
NEDg Description generation batch_69c0c23cc6d081909ce27bfb6a6f33d4 completed March 23, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_69c0c2deec7c81909d9949cb28f0211f completed March 23, 2026, 4:34 a.m.
Created at: March 22, 2026, 3:56 p.m.