Triple

T4544386
Position Surface form Disambiguated ID Type / Status
Subject Big Egg E110011 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: [Big Egg, region, Kanto region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanto region
Context triple: [Big Egg, region, Kanto region]
  • A. Kanto
    Kanto is a major geographical and metropolitan region of eastern Japan that includes Tokyo and several surrounding prefectures.
  • B. 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.
  • 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. Chūbu region
    The Chūbu region is a central area of Japan on Honshu Island, known for encompassing the Japanese Alps and including major prefectures such as Aichi, Nagano, and Shizuoka.
  • E. Hokuriku region
    The Hokuriku region is a coastal area in northwestern Honshu, Japan, known for its heavy snowfall, Sea of Japan shoreline, and historic castle and hot spring towns.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d517e881909c3d23ed4453b0a7 completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb936f3348190af0784d472bff312 completed March 20, 2026, 9:16 p.m.
Created at: March 20, 2026, 1:05 p.m.