Triple

T3189677
Position Surface form Disambiguated ID Type / Status
Subject Svealand E66788 entity
Predicate hasPart P35 FINISHED
Object Örebro County E100067 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: Örebro County | Statement: [Svealand, hasPart, Örebro County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Örebro County
Context triple: [Svealand, hasPart, Örebro County]
  • A. Örebro County chosen
    Örebro County is a county in central Sweden known for its industrial heritage, including major arms manufacturer Bofors, and its administrative center in the city of Örebro.
  • B. Uppsala County
    Uppsala County is an administrative region in east-central Sweden known for its historic university city of Uppsala and its mix of cultural heritage and rural landscapes.
  • C. Jönköping County
    Jönköping County is an administrative region in southern Sweden, centered around the city of Jönköping and known for its forests, lakes, and manufacturing industries.
  • D. Östergötland County
    Östergötland County is an administrative region in southeastern Sweden known for its mix of historic cities, fertile plains, and coastal and archipelago landscapes along the Baltic Sea.
  • E. Södermanland County
    Södermanland County is an administrative region in east-central Sweden known for its mix of coastal landscapes, forests, and historic towns such as Nyköping and Eskilstuna.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6e67e948190afbd9cc6a3ade415 completed March 8, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f0130db48190b6662c8dabf67d1d completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:07 p.m.