Triple

T1192743
Position Surface form Disambiguated ID Type / Status
Subject Kishiwada E25598 entity
Predicate locatedNear P294 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: [Kishiwada, locatedNear, Izumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Izumi
Context triple: [Kishiwada, locatedNear, 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. Nagaokakyo
    Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
  • E. Katsura River
    The Katsura River is a scenic river in Japan’s Kyoto Prefecture, famed for flowing through the Arashiyama district and its picturesque bridges, cherry blossoms, and traditional boat rides.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd761ef08190b431b80f326d1ab2 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde099eb88190ac354f3b4efb0965 completed March 8, 2026, 2:25 a.m.
Created at: March 1, 2026, 7:45 p.m.