Triple

T21358774
Position Surface form Disambiguated ID Type / Status
Subject Makino Nobuaki E526709 entity
Predicate memberOf P10 FINISHED
Object Kazoku NE NERFINISHED

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: Kazoku | Statement: [Makino Nobuaki, memberOf, Kazoku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kazoku
Context triple: [Makino Nobuaki, memberOf, Kazoku]
  • A. Kazoku chosen
    Kazoku was the hereditary peerage system of Japan’s Meiji era, comprising noble families ranked below the imperial family and above commoners.
  • B. Takasaki-chan
    Takasaki-chan is the official cute mascot character representing the city of Takasaki in Japan, often used to promote local culture and tourism.
  • C. Aishō
    Aishō is a town in Shiga Prefecture, Japan, known for its rural character and historical sites.
  • D. Kudanshita
    Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
  • E. Oi no Kobumi
    Oi no Kobumi is a travel diary by the renowned Japanese haiku poet Matsuo Bashō, recording his later journeys and reflections in prose and verse.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8afa3924c8190b3decbfda4a2aecf completed April 22, 2026, 11:23 a.m.
Created at: April 16, 2026, 5:07 p.m.