Triple

T21813780
Position Surface form Disambiguated ID Type / Status
Subject Marma E538544 entity
Predicate hasMunicipalitySeat P15510 FINISHED
Object Skutskär 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: Skutskär | Statement: [Marma, hasMunicipalitySeat, Skutskär]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skutskär
Context triple: [Marma, hasMunicipalitySeat, Skutskär]
  • A. Skutskär chosen
    Skutskär is a locality in Uppsala County, Sweden, known historically for its pulp and paper industry.
  • B. Österskär
    Österskär is a coastal locality in Österåker Municipality, Sweden, known as a residential seaside area within the Stockholm archipelago.
  • C. Kapellskär
    Kapellskär is a Swedish port on the Baltic Sea, north of Stockholm, that serves as a major ferry terminal for routes to Finland and the Baltic states.
  • D. Houtskär
    Houtskär is an island and former municipality in the Turku Archipelago of southwest Finland, known for its rugged coastal scenery and traditional Finnish-Swedish island culture.
  • E. Skärholmen
    Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
  • 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_69e0c473f0f8819086c9d1b4a143bd67 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f07cc8e6808190bde4d0e0981e4117 completed April 28, 2026, 9:24 a.m.
Created at: April 16, 2026, 6:54 p.m.