Triple

T7604710
Position Surface form Disambiguated ID Type / Status
Subject Gjesdal E180071 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Sandnes E397903 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: Sandnes | Statement: [Gjesdal, neighboringMunicipality, Sandnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandnes
Context triple: [Gjesdal, neighboringMunicipality, Sandnes]
  • A. Sandnes chosen
    Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
  • B. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
  • C. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • D. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • E. Sokndal
    Sokndal is a coastal municipality in Rogaland county in southwestern Norway, known for its rugged coastline, historic settlements, and distinctive geological landscapes.
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fbd1408190b721bf016f997c7b completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c97ca3d5e0819097e904184202b75f completed March 29, 2026, 7:25 p.m.
Created at: March 27, 2026, 3:54 p.m.