Triple

T6216516
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasCity P316 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: [Rogaland, hasCity, Sandnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandnes
Context triple: [Rogaland, hasCity, 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. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • D. Sokndal
    Sokndal is a coastal municipality in Rogaland county in southwestern Norway, known for its rugged coastline, historic settlements, and distinctive geological landscapes.
  • E. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • 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_69c7a303b960819082981f0efbdce014 completed March 28, 2026, 9:44 a.m.
Created at: March 22, 2026, 4:21 p.m.