Triple

T6305444
Position Surface form Disambiguated ID Type / Status
Subject Omiya Station E141363 entity
Predicate locatedIn P40 FINISHED
Object Saitama City E253810 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: Saitama City | Statement: [Omiya Station, locatedIn, Saitama City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saitama City
Context triple: [Omiya Station, locatedIn, Saitama City]
  • A. Ibaraki City
    Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • B. Hadano City
    Hadano City is a municipality in Kanagawa Prefecture, Japan, known for its natural scenery, including views of Mount Ōyama and surrounding mountainous landscapes.
  • C. Saitama (city) chosen
    Saitama is a major city in eastern Japan that serves as the capital of Saitama Prefecture and a key commercial and residential hub in the Greater Tokyo metropolitan area.
  • D. Ueda City
    Ueda City is a historic regional center in eastern Nagano Prefecture, Japan, known for Ueda Castle, samurai heritage, and its surrounding mountainous scenery.
  • E. Osaki New City
    Osaki New City is a major business and commercial district in Tokyo known for its modern office complexes, high-rise buildings, and urban redevelopment projects.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06479acec819090306a155a03b774 completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cc638e62608190958e90b07138a1cc completed April 1, 2026, 12:15 a.m.
Created at: March 22, 2026, 4:28 p.m.