Triple

T11153725
Position Surface form Disambiguated ID Type / Status
Subject Ehime Prefecture E263850 entity
Predicate hasCity P316 FINISHED
Object Saijō E1063390 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: Saijō | Statement: [Ehime Prefecture, hasCity, Saijō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saijō
Context triple: [Ehime Prefecture, hasCity, Saijō]
  • A. Saijo chosen
    Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
  • 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. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Isehara
    Isehara is a city in Kanagawa Prefecture, Japan, known as a residential and industrial area with access to nearby natural attractions such as the Tanzawa Mountains.
  • E. Wakamatsu
    Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e872ffbc8190b8a3bbd912115342 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a2796cc81908b6d4cf71f39e88a completed May 8, 2026, 5:52 a.m.
Created at: April 8, 2026, 9:28 p.m.