Triple

T9008003
Position Surface form Disambiguated ID Type / Status
Subject Sendai Mediatheque E215392 entity
Predicate notableWorkOf P4 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: [Sendai Mediatheque, notableWorkOf, Toyo Ito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyo Ito
Context triple: [Sendai Mediatheque, notableWorkOf, 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69bdc5fc819081015f4adacf9fd4 completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9a11948190a43f60d0df71b1af completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:06 p.m.