Triple

T17472471
Position Surface form Disambiguated ID Type / Status
Subject Tysnes Municipality E425453 entity
Predicate hasIsland P970 FINISHED
Object Reksteren 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: Reksteren | Statement: [Tysnes Municipality, hasIsland, Reksteren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reksteren
Context triple: [Tysnes Municipality, hasIsland, Reksteren]
  • A. Reksteren chosen
    Reksteren is a Norwegian island located in Vestland county, known for its rugged coastline and rural coastal communities.
  • B. Renkum
    Renkum is a municipality and town in the province of Gelderland in the eastern Netherlands, known for its riverside landscapes and proximity to the city of Arnhem.
  • C. Runsten
    Runsten is a small locality on the island of Öland in southeastern Sweden, known for its rural landscape and historical stone monuments.
  • D. Dromtacker
    Dromtacker is an area in Tralee, County Kerry, Ireland, known for hosting a main campus of Munster Technological University.
  • E. Ropscha
    Ropscha is a rural locality in Leningrad Oblast, Russia, historically known for its imperial estate associated with the Russian royal family.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451b8a51081908d94bebe2417e3d3 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.