Triple

T5039444
Position Surface form Disambiguated ID Type / Status
Subject Transformers E113508 entity
Predicate creator P184 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: [Transformers, creator, Hasbro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasbro
Context triple: [Transformers, creator, 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. 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.
  • C. Lego
    Lego is a globally popular line of interlocking plastic construction toys produced by The Lego Group, known for enabling creative building and inspiring a wide range of media, games, and themed experiences.
  • D. Warner Bros. Consumer Products
    Warner Bros. Consumer Products is the licensing and merchandising division of Warner Bros. that manages and commercializes the company’s entertainment brands and franchises worldwide.
  • E. Mattel Films
    Mattel Films is the film production division of the toy company Mattel, responsible for developing and producing movies based on its toy and game brands.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73dbf00c819094b67809dafdecc6 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c8084388190b25bbffc42f0b3ed completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.