Triple

T10705821
Position Surface form Disambiguated ID Type / Status
Subject Shigeru Ban E252400 entity
Predicate name P16 FINISHED
Object Shigeru Ban E252400 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: Shigeru Ban | Statement: [Shigeru Ban, name, Shigeru Ban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shigeru Ban
Context triple: [Shigeru Ban, name, Shigeru Ban]
  • A. Shigeru Ban chosen
    Shigeru Ban is a Japanese architect renowned for his innovative use of materials like paper and cardboard and for designing socially conscious, disaster-relief structures as well as major cultural buildings worldwide.
  • B. Toyo Ito
    Toyo Ito is a renowned Japanese architect celebrated for his innovative, fluid designs that blend technology, nature, and urban life.
  • C. Arata Isozaki
    Arata Isozaki is a renowned Japanese architect known for his influential and eclectic postmodern designs that bridge Eastern and Western architectural traditions.
  • D. Kazuyo Sejima
    Kazuyo Sejima is a renowned Japanese architect known for her minimalist, light-filled designs and as a founding partner of the firm SANAA.
  • E. Fumihiko Maki
    Fumihiko Maki is a renowned Japanese architect known for his modernist designs and thoughtful integration of technology, urban context, and public space.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fddeb060819094cd125a68070eb2 completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998fe56dc8190ae0c987b28ec6206 completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.