Triple

T6216549
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasMunicipality P847 FINISHED
Object Gjesdal E180071 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: Gjesdal | Statement: [Rogaland, hasMunicipality, Gjesdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gjesdal
Context triple: [Rogaland, hasMunicipality, Gjesdal]
  • A. Gjesdal chosen
    Gjesdal is a municipality in Rogaland county in southwestern Norway, known for its rural landscapes and proximity to the city of Stavanger.
  • B. Gausdal
    Gausdal is a rural municipality in southeastern Norway known for its agricultural landscape, forests, and outdoor recreational opportunities.
  • 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. Gjerdrum
    Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
  • E. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • 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_69c7eeb127248190bbee7a9f69c2b980 completed March 28, 2026, 3:07 p.m.
Created at: March 22, 2026, 4:21 p.m.