Triple

T16196972
Position Surface form Disambiguated ID Type / Status
Subject Nordlandet E393085 entity
Predicate connectsTo P845 FINISHED
Object Kirkelandet E373442 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: Kirkelandet | Statement: [Nordlandet, connectsTo, Kirkelandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirkelandet
Context triple: [Nordlandet, connectsTo, Kirkelandet]
  • A. Kirkelandet chosen
    Kirkelandet is the central island and main urban area of the Norwegian coastal city of Kristiansund.
  • B. Bjerkvik
    Bjerkvik is a small village in Narvik Municipality in Nordland county, northern Norway, situated at the head of the Herjangsfjord.
  • C. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • D. Köpingsvik
    Köpingsvik is a coastal village and popular holiday resort on the Swedish island of Öland, known for its sandy beaches and historic church.
  • E. Haukland
    Haukland is a small coastal village on the island of Vestvågøy in Norway’s Lofoten archipelago, known for its scenic beach and dramatic surrounding mountains.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222dace848190b1a98e47333b922b completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ecf454081909660f4ab9c556ddc completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:02 a.m.