Triple

T15360781
Position Surface form Disambiguated ID Type / Status
Subject Norwegian County Road 63 E367282 entity
Predicate passesThrough P225 FINISHED
Object Valldal E523889 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: Valldal | Statement: [Norwegian County Road 63, passesThrough, Valldal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valldal
Context triple: [Norwegian County Road 63, passesThrough, Valldal]
  • A. Valldal chosen
    Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
  • B. Gravdal
    Gravdal is a small coastal village on the island of Vestvågøy in Norway’s Lofoten archipelago.
  • C. Engerdal
    Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
  • D. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • E. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4607408190ab281a7f7a8012d3 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00a502c82881908d5b6f7c23e8a403 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 3:18 a.m.