Triple

T16009211
Position Surface form Disambiguated ID Type / Status
Subject Allspark Pictures E388296 entity
Predicate parentCompany P254 FINISHED
Object Hasbro E120132 NE FINISHED

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: Hasbro | Statement: [Allspark Pictures, parentCompany, Hasbro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasbro
Context triple: [Allspark Pictures, parentCompany, Hasbro]
  • A. Hasbro chosen
    Hasbro is a major American toy and entertainment company known for creating and owning popular brands such as Transformers, My Little Pony, and Monopoly.
  • B. Kenner Products
    Kenner Products was an American toy company best known for producing popular licensed toy lines such as the original Star Wars action figures.
  • C. Mattel Interactive
    Mattel Interactive was the video game publishing division of the toy company Mattel, known for releasing games based on its popular toy and entertainment franchises.
  • D. Takara Tomy
    Takara Tomy is a Japanese toy and entertainment company best known internationally for creating and producing the Transformers franchise and other popular toy lines.
  • E. Bandai America
    Bandai America is the North American subsidiary of the Japanese toy and entertainment company Bandai, responsible for marketing and distributing popular toy lines and licensed products in the U.S. and surrounding regions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1828e9e708190aec0078913bf098a completed April 17, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf24a9d8819083d7b11d71442da6 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:55 a.m.