Triple

T11566869
Position Surface form Disambiguated ID Type / Status
Subject Kyoto metropolitan area E274274 entity
Predicate coreCity P235 FINISHED
Object Kyōtanabe E141768 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: Kyōtanabe | Statement: [Kyoto metropolitan area, coreCity, Kyōtanabe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyōtanabe
Context triple: [Kyoto metropolitan area, coreCity, Kyōtanabe]
  • A. Kyotanabe chosen
    Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
  • B. Kitanagoya
    Kitanagoya is a city in central Japan known as a residential and commercial suburb within the Nagoya metropolitan area.
  • C. Koshigaya
    Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
  • D. Higashikawa
    Higashikawa is a town in Hokkaido, Japan, known as a gateway to the Daisetsuzan mountain range and for its scenic natural landscapes.
  • 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 (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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fedd19164481909c2f35fbebf6150e completed May 9, 2026, 7:07 a.m.
Created at: April 8, 2026, 9:37 p.m.