Triple

T15529032
Position Surface form Disambiguated ID Type / Status
Subject Strand E370161 entity
Predicate borders P224 FINISHED
Object Hjelmeland E593849 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: Hjelmeland | Statement: [Strand, borders, Hjelmeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hjelmeland
Context triple: [Strand, borders, Hjelmeland]
  • A. Hjelmeland chosen
    Hjelmeland is a rural municipality in southwestern Norway known for its fjord landscapes, agriculture, and traditional fruit farming.
  • B. Jørpeland
    Jørpeland is a town in Rogaland county, Norway, known as a local industrial and service hub and a gateway to the nearby Lysefjord and Preikestolen (Pulpit Rock).
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • E. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414620588190958ffde651ccab5f completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90887ef48190b6148830803669dd completed May 9, 2026, 7:52 p.m.
Created at: April 10, 2026, 4:05 a.m.