Triple

T6216539
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasMunicipality P847 FINISHED
Object Randaberg E348342 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: Randaberg | Statement: [Rogaland, hasMunicipality, Randaberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randaberg
Context triple: [Rogaland, hasMunicipality, Randaberg]
  • A. Randaberg chosen
    Randaberg is a coastal municipality in Rogaland county, Norway, situated just north of the city of Stavanger and known for its agriculture and scenic shoreline.
  • B. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • C. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • D. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • E. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a1eb3881908c7f735cf9c429ce completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3dd76508190aba82a4a74c74bea completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:21 p.m.