Triple

T20062579
Position Surface form Disambiguated ID Type / Status
Subject Kose Parish E499517 entity
Predicate hasAdministrativeCentre P1474 FINISHED
Object Kose NE NERFINISHED

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: Kose | Statement: [Kose Parish, hasAdministrativeCentre, Kose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kose
Context triple: [Kose Parish, hasAdministrativeCentre, Kose]
  • A. Kose chosen
    Kose is a settlement in northern Estonia known for lending its name to the historic Pirita-Kose-Kloostrimetsa motor racing circuit near Tallinn.
  • B. Neikea
    Neikea are minor Greek deities or personifications associated with quarrels, feuds, and grievances, traditionally counted among the many troublesome offspring of the goddess Eris.
  • C. Shiseido
    Shiseido is a major Japanese multinational cosmetics and skincare company known for its high-end beauty products and long-standing global presence.
  • D. Kao
    Kao is a volcanic island in the Haʻapai group of Tonga, notable for being one of the country's highest and most prominent volcanic peaks.
  • E. Kao
    Kao is a Chinese surname borne by numerous individuals, including notable figures in science, business, and the arts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66376f2d4819081b9e1b265650e5b completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.