Triple

T13556064
Position Surface form Disambiguated ID Type / Status
Subject Mitsubishi Group E323776 entity
Predicate hasMember P10 FINISHED
Object Nikon Corporation E554260 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: Nikon Corporation | Statement: [Mitsubishi Group, hasMember, Nikon Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nikon Corporation
Context triple: [Mitsubishi Group, hasMember, Nikon Corporation]
  • A. Nikon Corporation chosen
    Nikon Corporation is a Japanese multinational company renowned for its cameras, imaging products, and precision optical equipment.
  • B. Fujifilm
    Fujifilm is a Japanese multinational company best known for its photographic film, digital imaging products, and diversified technologies in healthcare and printing.
  • C. Olympus Corporation
    Olympus Corporation is a Japanese multinational company best known for its optical and imaging products, including cameras, medical endoscopes, and scientific equipment.
  • D. Leica Camera AG
    Leica Camera AG is a renowned German manufacturer of premium cameras and sport optics, celebrated for its precision engineering and iconic photographic equipment.
  • E. Canon Inc.
    Canon Inc. is a Japanese multinational corporation renowned for its imaging and optical products, including cameras, camcorders, printers, and related equipment.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff3063c8190bd20149b3f7df352 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75da95b7c8190af4fae155f01d3af completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:47 p.m.