Triple

T13768421
Position Surface form Disambiguated ID Type / Status
Subject Hadseløya E330810 entity
Predicate hasSettlement P1068 FINISHED
Object Stokmarknes E340039 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: Stokmarknes | Statement: [Hadseløya, hasSettlement, Stokmarknes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stokmarknes
Context triple: [Hadseløya, hasSettlement, Stokmarknes]
  • A. Svolvær
    Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
  • B. Tingvoll
    Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
  • C. Øksnes chosen
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • D. Steenodde
    Steenodde is a small coastal village on the North Sea island of Amrum in Germany, known for its tranquil atmosphere and maritime surroundings.
  • E. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0233ecc48190b934f085d2501eb1 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd192957008190b525778430b56ca0 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:10 p.m.