Triple

T14126057
Position Surface form Disambiguated ID Type / Status
Subject Närke E340035 entity
Predicate hasMunicipality P847 FINISHED
Object Lekeberg Municipality E444804 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: Lekeberg Municipality | Statement: [Närke, hasMunicipality, Lekeberg Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lekeberg Municipality
Context triple: [Närke, hasMunicipality, Lekeberg Municipality]
  • A. Lekeberg Municipality chosen
    Lekeberg Municipality is a local government area in central Sweden known for its rural landscapes and location within Örebro County.
  • B. Berg Municipality
    Berg Municipality is a local government area in central Sweden known for its mountainous landscapes, lakes, and outdoor recreation within Jämtland County.
  • C. Norberg Municipality
    Norberg Municipality is a local government area in Västmanland County, central Sweden, known for its historic mining communities and forested rural landscape.
  • D. Mora Municipality
    Mora Municipality is a local administrative region in Portugal known for its rural landscapes, traditional Alentejo culture, and archaeological and natural heritage.
  • E. Kinn Municipality
    Kinn Municipality is a coastal municipality in western Norway known for its rugged coastline, fishing communities, and maritime industries.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6096976481909dc79066c5165a50 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd2801198481909f9151ca873bfc56 completed May 8, 2026, 12:02 a.m.
Created at: April 9, 2026, 10:22 p.m.