Triple

T21545442
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate nearbyMunicipality P4647 FINISHED
Object Rælingen 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: Rælingen | Statement: [Oslomarka, nearbyMunicipality, Rælingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rælingen
Context triple: [Oslomarka, nearbyMunicipality, Rælingen]
  • A. Rælingen chosen
    Rælingen is a municipality in Viken county, Norway, known for its proximity to Oslo and its mix of residential areas, forests, and lakes.
  • B. Rendalen
    Rendalen is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and outdoor recreation opportunities.
  • C. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • D. Ranemsletta
    Ranemsletta is a village in Trøndelag county, Norway, serving as the main local hub for services and governance in the municipality of Overhalla.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58e38808190888f3501cf4fff7c completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.