Triple

T9704068
Position Surface form Disambiguated ID Type / Status
Subject Cecil Balmond E234852 entity
Predicate collaboratedWith P435 FINISHED
Object Toyo Ito E145952 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: Toyo Ito | Statement: [Cecil Balmond, collaboratedWith, Toyo Ito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyo Ito
Context triple: [Cecil Balmond, collaboratedWith, Toyo Ito]
  • A. Toyo Ito chosen
    Toyo Ito is a renowned Japanese architect celebrated for his innovative, fluid designs that blend technology, nature, and urban life.
  • B. 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.
  • 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. Fumihiko Maki
    Fumihiko Maki is a renowned Japanese architect known for his modernist designs and thoughtful integration of technology, urban context, and public space.
  • E. Shigeru Ban
    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.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19136b40c8190922052dd84d49f15 completed April 4, 2026, 10:31 p.m.
Created at: March 30, 2026, 8:18 p.m.