Triple

T6804982
Position Surface form Disambiguated ID Type / Status
Subject Kalsoy E156280 entity
Predicate hasViewTowards P854 FINISHED
Object Kunoy E608011 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: Kunoy | Statement: [Kalsoy, hasViewTowards, Kunoy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kunoy
Context triple: [Kalsoy, hasViewTowards, Kunoy]
  • A. Kunoy chosen
    Kunoy is a small, mountainous island in the Faroe Islands known for its dramatic cliffs, sparse population, and traditional fishing villages.
  • B. Konomihu
    Konomihu is an extinct Native American language variety traditionally spoken in northern California, considered a dialect of the Shasta language.
  • C. Oyugis
    Oyugis is a town in western Kenya that serves as a key commercial and administrative center in the former Rachuonyo District of Homa Bay County.
  • D. Kujūkuri
    Kujūkuri is a long, sandy coastal town and beach area on the eastern shore of Chiba Prefecture, Japan, known for its surfing spots and scenic Pacific shoreline.
  • E. Yokote
    Yokote is a city in Akita Prefecture, Japan, known for its heavy snowfall and the annual Yokote Kamakura Snow Festival featuring traditional igloo-like snow huts.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2ea459c819095388218d53c250a completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a9ff30c8190aaf2687dd41fc07a completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:16 p.m.