Triple

T1366299
Position Surface form Disambiguated ID Type / Status
Subject Sendagaya E30009 entity
Predicate region P40 FINISHED
Object Kanto 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 | Statement: [Sendagaya, region, Kanto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanto
Context triple: [Sendagaya, region, Kanto]
  • A. Kanto
    Kanto is a major geographical and metropolitan region of eastern Japan that includes Tokyo and several surrounding prefectures.
  • B. Geita Region
    Geita Region is an administrative region in northwestern Tanzania, known for its significant gold mining activities and proximity to Lake Victoria.
  • C. Volta Region
    The Volta Region is an eastern administrative region of Ghana known for its diverse Ewe culture, lush landscapes, and attractions such as Lake Volta and Wli Waterfalls.
  • D. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • E. 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.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d1d15481909d58b6fd8aa2e585 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08a7ed5c8190b9f99a6f4524eae8 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 7:57 p.m.