Triple

T21382966
Position Surface form Disambiguated ID Type / Status
Subject Gifu Prefecture E527409 entity
Predicate hasCity P316 FINISHED
Object Nakatsugawa NE NERFINISHED

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: Nakatsugawa | Statement: [Gifu Prefecture, hasCity, Nakatsugawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakatsugawa
Context triple: [Gifu Prefecture, hasCity, Nakatsugawa]
  • A. Nakatsugawa
    Nakatsugawa is a river associated with the city of Atsugi in Kanagawa Prefecture, Japan.
  • B. Nakatsugawa chosen
    Nakatsugawa is a city in Gifu Prefecture, Japan, known as a historic post town gateway to the scenic Kiso Valley and the Nakasendō route.
  • C. Takaido
    Takaido is a residential neighborhood in Tokyo, Japan, known for its quiet streets, local shopping areas, and convenient train access.
  • D. Gushikawa
    Gushikawa was a former city in Okinawa Prefecture, Japan, that later became part of the modern city of Uruma.
  • E. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0f05278819096c511035ffc9777 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:12 p.m.