Triple

T5616142
Position Surface form Disambiguated ID Type / Status
Subject Ekerö Island E147481 entity
Predicate hasPostalArea P920 FINISHED
Object Ekerö E26096 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: Ekerö | Statement: [Ekerö Island, hasPostalArea, Ekerö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ekerö
Context triple: [Ekerö Island, hasPostalArea, Ekerö]
  • A. Ekerö Municipality chosen
    Ekerö Municipality is a suburban island municipality in eastern Sweden known for its natural landscapes and historic sites, located just west of central Stockholm.
  • B. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • C. Eskilstuna
    Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Karlskoga
    Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021da7f848190bb1cd0270ad6398f completed March 22, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d55b95c8190a5f3e2c05249c136 completed March 22, 2026, 8:13 p.m.
Created at: March 22, 2026, 3:39 p.m.