Triple

T1300151
Position Surface form Disambiguated ID Type / Status
Subject Södermanland County E27742 entity
Predicate hasUrbanArea P316 FINISHED
Object Eskilstuna E203558 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: Eskilstuna | Statement: [Södermanland County, hasUrbanArea, Eskilstuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eskilstuna
Context triple: [Södermanland County, hasUrbanArea, Eskilstuna]
  • A. Eskilstuna chosen
    Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
  • B. Enköping
    Enköping is a small Swedish town known for its numerous themed parks and gardens, often called “Sweden’s nearest town” due to its central location relative to several major cities.
  • C. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • D. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • E. Jönköping
    Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical hub.
  • 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_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c11314a48190ab4efb8b1acdce50 completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69addf2374ac8190ac2a2a753c056a3d completed March 8, 2026, 8:42 p.m.
Created at: March 1, 2026, 7:51 p.m.