Triple

T14577623
Position Surface form Disambiguated ID Type / Status
Subject Larry Kaplan E342096 entity
Predicate notableWork P4 FINISHED
Object Kaboom!
Kaboom! is a fast-paced 1981 Atari 2600 action video game in which players catch falling bombs with buckets, widely regarded as one of the console’s classic titles.
 E1106145 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: Kaboom! | Statement: [Larry Kaplan, notableWork, Kaboom!]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kaboom!
Context triple: [Larry Kaplan, notableWork, Kaboom!]
  • A. Kaboom
    Kaboom is a 2010 surreal coming-of-age dark comedy film written and directed by Gregg Araki.
  • B. Ka-boom Ka-boom
    "Ka-boom Ka-boom" is a track by Marilyn Manson featured on his 2003 industrial metal album *The Golden Age of Grotesque*.
  • C. Kaboom Town!
    Kaboom Town! is an annual Independence Day fireworks and entertainment festival held in Addison, Texas, known for one of the most spectacular pyrotechnic displays in the United States.
  • D. Boom-Boom
    Boom-Boom is a Marvel Comics mutant superhero known for generating explosive energy "time-bombs" and serving on teams like the New Mutants and X-Force.
  • E. The Boom
    The Boom was a Japanese rock band best known for their 1993 hit single "Shima Uta," which blended rock with Okinawan folk influences.
  • 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: Kaboom!
Triple: [Larry Kaplan, notableWork, Kaboom!]
Generated description
Kaboom! is a fast-paced 1981 Atari 2600 action video game in which players catch falling bombs with buckets, widely regarded as one of the console’s classic titles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kaboom!
Target entity description: Kaboom! is a fast-paced 1981 Atari 2600 action video game in which players catch falling bombs with buckets, widely regarded as one of the console’s classic titles.
  • A. Kaboom
    Kaboom is a 2010 surreal coming-of-age dark comedy film written and directed by Gregg Araki.
  • B. Ka-boom Ka-boom
    "Ka-boom Ka-boom" is a track by Marilyn Manson featured on his 2003 industrial metal album *The Golden Age of Grotesque*.
  • C. Kaboom Town!
    Kaboom Town! is an annual Independence Day fireworks and entertainment festival held in Addison, Texas, known for one of the most spectacular pyrotechnic displays in the United States.
  • D. Boom-Boom
    Boom-Boom is a Marvel Comics mutant superhero known for generating explosive energy "time-bombs" and serving on teams like the New Mutants and X-Force.
  • E. The Boom
    The Boom was a Japanese rock band best known for their 1993 hit single "Shima Uta," which blended rock with Okinawan folk influences.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f5ec448190b2ef887fdf7b633e completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ace7da48190880a736ead5c4055 completed May 8, 2026, 7:03 a.m.
NEDg Description generation batch_69fd8bb3c1188190b158d30e9c962911 completed May 8, 2026, 7:07 a.m.
NED2 Entity disambiguation (via description) batch_69fd8c6e7d448190835f87e27c998623 completed May 8, 2026, 7:10 a.m.
Created at: April 10, 2026, 1:24 a.m.