Triple

T13043576
Position Surface form Disambiguated ID Type / Status
Subject Landmark Tower E327258 entity
Predicate structuralEngineer P616 FINISHED
Object Mitsubishi Jisho Sekkei E326398 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 Jisho Sekkei | Statement: [Landmark Tower, structuralEngineer, Mitsubishi Jisho Sekkei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitsubishi Jisho Sekkei
Context triple: [Landmark Tower, structuralEngineer, Mitsubishi Jisho Sekkei]
  • A. Mitsubishi Jisho Sekkei chosen
    Mitsubishi Jisho Sekkei is a major Japanese architectural and urban design firm known for creating prominent high-rise and commercial developments across Japan.
  • B. 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.
  • C. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • D. Mitsushō
    Mitsushō was a former town in Hokkaido, Japan, that later became part of the newly created town of Shinhidaka through a municipal merger.
  • E. 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.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d98050157c8190bb8c640b759ac2b7 completed April 10, 2026, 10:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5fdd04c8190a86dbba1b81c8e6b completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 8:56 p.m.