Triple

T5780436
Position Surface form Disambiguated ID Type / Status
Subject Mitsubishi G4M E127541 entity
Predicate designBureau P25389 FINISHED
Object Mitsubishi E130915 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: Mitsubishi | Statement: [Mitsubishi G4M, designBureau, Mitsubishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitsubishi
Context triple: [Mitsubishi G4M, designBureau, Mitsubishi]
  • A. Mitsubishi chosen
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • B. Mitsubishi Motors
    Mitsubishi Motors is a Japanese automotive manufacturer known for producing a wide range of passenger cars, SUVs, and light commercial vehicles and for its involvement in global automotive alliances.
  • C. Fuji Heavy Industries
    Fuji Heavy Industries is a Japanese transportation conglomerate best known as the former parent company of Subaru, involved in automotive, aerospace, and industrial products.
  • D. Mitsubishi Jisho Sekkei
    Mitsubishi Jisho Sekkei is a major Japanese architectural and urban design firm known for creating prominent high-rise and commercial developments across Japan.
  • E. Nissan
    Nissan is a major Japanese automobile manufacturer known for producing a wide range of passenger cars, trucks, and electric vehicles sold globally.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e3f88c8190975921ff2912e543 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bfa9d9348190b8916accca9374f2 completed March 23, 2026, 4:20 a.m.
Created at: March 22, 2026, 3:50 p.m.