Triple

T15479949
Position Surface form Disambiguated ID Type / Status
Subject Kamogawa E376888 entity
Predicate near P350 FINISHED
Object Gion district E83963 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: Gion district | Statement: [Kamogawa, near, Gion district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gion district
Context triple: [Kamogawa, near, Gion district]
  • A. Gion district chosen
    Gion district is Kyoto’s famous traditional entertainment quarter, renowned for its historic wooden machiya houses, teahouses, and geisha (geiko and maiko) culture.
  • B. Komagome district
    Komagome district is a residential and commercial neighborhood in Tokyo, Japan, known for its traditional atmosphere, historic temples, and proximity to Rikugien Garden.
  • C. Koishikawa district
    Koishikawa district is a residential and educational neighborhood in Tokyo known for sites like Koishikawa Kōrakuen Garden and the University of Tokyo facilities.
  • D. Kawaramachi area
    The Kawaramachi area is a bustling commercial and entertainment district in central Kyoto known for its shopping streets, restaurants, and proximity to traditional nightlife alleys like Pontocho.
  • E. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8a77a081909f12f13660452f4a completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00d445c4848190b5c97bb27be6c749 completed May 10, 2026, 6:53 p.m.
Created at: April 10, 2026, 3:34 a.m.