Triple

T4967087
Position Surface form Disambiguated ID Type / Status
Subject Giants E111554 entity
Predicate region P40 FINISHED
Object Kanto E51702 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 | Statement: [Giants, region, Kanto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanto
Context triple: [Giants, region, Kanto]
  • A. Kanto chosen
    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. Geita Region
    Geita Region is an administrative region in northwestern Tanzania, known for its significant gold mining activities and proximity to Lake Victoria.
  • 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. Kantōgun
    Kantōgun was the Imperial Japanese Army's Kwantung Army, a powerful and influential military force stationed in Manchuria that played a central role in Japan's expansionist policies before and during World War II.
  • 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71f8f550819099235511ca271e2d completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be92489ae481909240f2ad20637649 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:32 p.m.