Triple

T15999465
Position Surface form Disambiguated ID Type / Status
Subject Hitachi SH-4 E388057 entity
Predicate usedBy P260 FINISHED
Object Sammy Corporation E931568 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: Sammy Corporation | Statement: [Hitachi SH-4, usedBy, Sammy Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sammy Corporation
Context triple: [Hitachi SH-4, usedBy, Sammy Corporation]
  • A. Sammy Corporation chosen
    Sammy Corporation is a Japanese entertainment and gaming company best known for manufacturing pachinko and pachislot machines and for its involvement in the broader video game industry.
  • B. Sammy Entertainment USA
    Sammy Entertainment USA was the earlier corporate name of the American video game developer now known as High Moon Studios.
  • C. Sam's West, Inc.
    Sam's West, Inc. is the corporate subsidiary of Walmart Inc. responsible for operating the Sam's Club chain of membership-only warehouse clubs.
  • D. Sally Corporation
    Sally Corporation is an American themed entertainment company best known for designing and manufacturing dark rides and animatronic attractions for theme parks worldwide.
  • E. Snow Corporation
    Snow Corporation is a South Korean tech company best known for its mobile photo and video apps, including the popular selfie and augmented reality camera app SNOW.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1578a0adc819097c6a23514182173 completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d99ca08190a3d07a0802b1b24a completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:55 a.m.