Triple

T13271386
Position Surface form Disambiguated ID Type / Status
Subject Syusen E316064 entity
Predicate developedBy P73 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: [Syusen, developedBy, Mitsubishi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitsubishi
Context triple: [Syusen, developedBy, 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. Mitsubishi Zuisei
    The Mitsubishi Zuisei was a Japanese air-cooled radial aircraft engine widely used in Imperial Japanese Navy aircraft during the World War II era.
  • D. 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.
  • E. 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.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99020f710819094c2618662bdc7fd completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716cd8c2c8190a28d901fde98dc26 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:26 p.m.