Triple

T6339622
Position Surface form Disambiguated ID Type / Status
Subject Waseda Campus E142589 entity
Predicate region P40 FINISHED
Object Kanto region E54245 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: Kanto region | Statement: [Waseda Campus, region, Kanto region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanto region
Context triple: [Waseda Campus, region, Kanto region]
  • A. Kanto
    Kanto is a major geographical and metropolitan region of eastern Japan that includes Tokyo and several surrounding prefectures.
  • B. Kanto Plain
    The Kanto Plain is Japan's largest and most populous lowland region, encompassing Tokyo and surrounding urban and agricultural areas on central Honshu.
  • C. Kantō region chosen
    The Kantō region is a major geographical and economic area of eastern Honshu, Japan, encompassing Tokyo and several surrounding prefectures and serving as the country’s political and population center.
  • D. Yamato region
    The Yamato region is the early political and cultural heartland of Japan, where the first unified Japanese state emerged under the Yamato court.
  • E. North Kantō
    North Kantō is a subregion in eastern Japan generally referring to the inland northern prefectures of the Kantō region, known for their mix of industrial cities, agriculture, and natural landscapes.
  • 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0654fb774819087bffb8b966a790a completed March 22, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c604352f148190b5accc28462256ad completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.