Triple

T17370983
Position Surface form Disambiguated ID Type / Status
Subject Krødsherad E422312 entity
Predicate hasCapital P204 FINISHED
Object Noresund 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: Noresund | Statement: [Krødsherad, hasCapital, Noresund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noresund
Context triple: [Krødsherad, hasCapital, Noresund]
  • A. Noresund chosen
    Noresund is a small village in Viken county, Norway, known as a local service and tourism hub near the lake Krøderen and the Norefjell mountain area.
  • B. Norrsundet
    Norrsundet is a small coastal locality in eastern Sweden known historically for its sawmill and harbor along the Gulf of Bothnia.
  • C. Kvernes
    Kvernes is a village and historic parish area in Averøy Municipality in Møre og Romsdal county, Norway, known for its cultural heritage and scenic coastal landscape.
  • D. Randesund
    Randesund is a coastal district of Kristiansand in southern Norway, known for its scenic archipelago, beaches, and recreational outdoor areas.
  • E. Sundet
    Sundet is the main town and local hub of Eidsvoll municipality in Norway, serving as its commercial and service center.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a68ff448190b505861e56df5b6d completed April 19, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:44 a.m.