Triple

T21953991
Position Surface form Disambiguated ID Type / Status
Subject Langåra E542135 entity
Predicate hasNameInLanguage P15 FINISHED
Object Langåra (Norwegian) 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: Langåra (Norwegian) | Statement: [Langåra, hasNameInLanguage, Langåra (Norwegian)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langåra (Norwegian)
Context triple: [Langåra, hasNameInLanguage, Langåra (Norwegian)]
  • A. Langåra chosen
    Langåra is an island located within the municipality of Asker in Viken county, Norway.
  • B. Salangen
    Salangen is a coastal municipality in Troms county in northern Norway, known for its fjords, fishing traditions, and the administrative center village of Sjøvegan.
  • C. Hauge i Dalane
    Hauge i Dalane is a village in Rogaland county, Norway, known as the main settlement of the Sokndal municipality in the Dalane district.
  • D. Fjørå
    Fjørå is a small Norwegian village situated along the inner reaches of a fjord in Møre og Romsdal county.
  • E. Lyngen
    Lyngen is a municipality in Troms og Finnmark county in northern Norway, known for its dramatic fjord landscapes and surrounding alpine mountains.
  • 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_69e0c47ef0e48190a50e1bcc43f4b3fd completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1243dfb4081909bc7a722843ffea7 completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:59 p.m.