Triple

T6983368
Position Surface form Disambiguated ID Type / Status
Subject National Stadium (Tokyo) E161900 entity
Predicate architect P184 FINISHED
Object Kengo Kuma E386044 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: Kengo Kuma | Statement: [National Stadium (Tokyo), architect, Kengo Kuma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kengo Kuma
Context triple: [National Stadium (Tokyo), architect, Kengo Kuma]
  • A. Kengo Kuma chosen
    Kengo Kuma is a renowned Japanese architect known for his innovative use of natural materials and harmonious integration of buildings with their surrounding environments.
  • B. Tadao Kashio
    Tadao Kashio was a Japanese engineer and entrepreneur best known for co-founding Casio and pioneering innovative electronic calculators and consumer electronics.
  • C. Kazuyo Kawashima
    Kazuyo Kawashima is a Japanese woman best known as the mother of Princess Kiko, a member of Japan’s Imperial Family.
  • D. Toyo Ito
    Toyo Ito is a renowned Japanese architect celebrated for his innovative, fluid designs that blend technology, nature, and urban life.
  • E. Nendo
    Nendo is the largest island in the Santa Cruz Islands of the Solomon Islands, located in Temotu Province in the southwestern Pacific Ocean.
  • 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_69c68855dc0481909b4c7e9e9ed273db completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db90e9108190a7aedeef1fb17eb4 completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761c671588190a4e7b5c26cdfe6ba completed March 28, 2026, 5:06 a.m.
Created at: March 27, 2026, 2:31 p.m.