Triple

T11566872
Position Surface form Disambiguated ID Type / Status
Subject Kyoto metropolitan area E274274 entity
Predicate coreCity P235 FINISHED
Object Ayabe E319177 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: Ayabe | Statement: [Kyoto metropolitan area, coreCity, Ayabe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ayabe
Context triple: [Kyoto metropolitan area, coreCity, Ayabe]
  • A. Ayabe chosen
    Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
  • B. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • C. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • D. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • E. Ichinomiya
    Ichinomiya is a city in Aichi Prefecture, Japan, known historically as a textile and commercial center within the Nagoya metropolitan area.
  • 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_6a00aade82788190a5f3cedbc22065c4 completed May 10, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:37 p.m.