Triple

T10945213
Position Surface form Disambiguated ID Type / Status
Subject Sarushima E258577 entity
Predicate locatedInAdministrativeTerritorialEntity 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: [Sarushima, locatedInAdministrativeTerritorialEntity, Yokosuka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yokosuka
Context triple: [Sarushima, locatedInAdministrativeTerritorialEntity, 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 was a Japanese aircraft manufacturer best known for producing military seaplanes and bombers for the Imperial Japanese Navy during World War II.
  • E. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770e9a89081908979efd1d9e6af66 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f470cbce14819099d47d468ae61df7 completed May 1, 2026, 9:22 a.m.
Created at: April 8, 2026, 9:23 p.m.