Triple

T16027256
Position Surface form Disambiguated ID Type / Status
Subject Vågsøy E388746 entity
Predicate hasBay P35 FINISHED
Object Sildegapet E1149866 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: Sildegapet | Statement: [Vågsøy, hasBay, Sildegapet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sildegapet
Context triple: [Vågsøy, hasBay, Sildegapet]
  • A. Sildegapet chosen
    Sildegapet is a coastal sea area adjacent to the municipality of Stad in western Norway, known for its rough waters and significance to local maritime routes.
  • B. Rapadalen
    Rapadalen is a renowned, remote river valley in northern Sweden known for its dramatic alpine scenery and rich wildlife within Sarek National Park.
  • C. Harpefoss
    Harpefoss is a small village in Sør-Fron Municipality in Innlandet county, Norway, known for its scenic valley setting along the Gudbrandsdalslågen river.
  • D. Tallkrogen
    Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
  • E. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf33c6a881909284933ea3b7dd6e completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:56 a.m.