Triple

T4873976
Position Surface form Disambiguated ID Type / Status
Subject Oppama, Japan E109155 entity
Predicate locatedIn P40 FINISHED
Object Yokosuka E281970 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: Yokosuka | Statement: [Oppama, Japan, locatedIn, Yokosuka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yokosuka
Context triple: [Oppama, Japan, locatedIn, Yokosuka]
  • A. Yokosuka chosen
    Yokosuka is a coastal city in Kanagawa Prefecture, Japan, known for its major naval base and strategic location at the mouth of Tokyo Bay.
  • B. Tachikawa
    Tachikawa is a major city in western Tokyo, Japan, known as a key commercial and transportation hub of the Tama region.
  • C. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • D. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka metropolitan area.
  • E. Yokosuka Port
    Yokosuka Port is a major Japanese maritime hub in Kanagawa Prefecture known for its commercial shipping facilities and significant naval bases, including those of the Japan Maritime Self-Defense Force and the U.S. Navy.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d9fa0b08190ab1fc7ec395dca37 completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89d9e6688190b8a8ad3137148e50 completed March 21, 2026, 12:06 p.m.
Created at: March 20, 2026, 1:27 p.m.