Triple

T2457536
Position Surface form Disambiguated ID Type / Status
Subject Sakai, Osaka Prefecture, Japan E54456 entity
Predicate borderedBy P224 FINISHED
Object Izumi E8408 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: Izumi | Statement: [Sakai, Osaka Prefecture, Japan, borderedBy, Izumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Izumi
Context triple: [Sakai, Osaka Prefecture, Japan, borderedBy, Izumi]
  • A. Izumi chosen
    Izumi is a city located in Osaka Prefecture, Japan, known as a residential and commercial hub in the Kansai region.
  • B. Izumiotsu
    Izumiotsu is a coastal city in Osaka Prefecture, Japan, known for its port facilities and industrial waterfront along Osaka Bay.
  • C. Kizugawa
    Kizugawa is a city in southern Kyoto Prefecture, Japan, known for its mix of historical sites, residential areas, and growing industrial and research facilities.
  • D. Guri
    Guri is a city in South Korea located just east of Seoul, known as a suburban residential area with historical sites and access to natural scenery.
  • E. Nagaokakyo
    Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd10860188190bfc4c554914487b4 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b44ec039e881909660350b98d79ba1 completed March 13, 2026, 5:52 p.m.
Created at: March 6, 2026, 9:44 p.m.