Triple

T20391287
Position Surface form Disambiguated ID Type / Status
Subject Thomas Dekker E498088 entity
Predicate actedIn P1668 FINISHED
Object Kaboom 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: Kaboom | Statement: [Thomas Dekker, actedIn, Kaboom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaboom
Context triple: [Thomas Dekker, actedIn, Kaboom]
  • A. Kaboom chosen
    Kaboom is a 2010 surreal coming-of-age dark comedy film written and directed by Gregg Araki.
  • B. 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.
  • C. 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*.
  • D. KaBoom
    KaBoom is the energetic mascot of the Lancaster JetHawks minor league baseball team, known for entertaining fans with lively antics at games.
  • E. Kaboings
    Kaboings are a type of Kremling enemy from the Donkey Kong video game series, known for their distinctive bouncing movement and dual-headed appearance.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790f8d9c819093038f6bb6f47a92 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.