Triple

T4588678
Position Surface form Disambiguated ID Type / Status
Subject Karlskoga E103430 entity
Predicate locatedWestOf P4239 FINISHED
Object Örebro E370085 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 | Statement: [Karlskoga, locatedWestOf, Örebro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Örebro
Context triple: [Karlskoga, locatedWestOf, Örebro]
  • A. Örebro chosen
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • B. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • D. 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.
  • E. Skövde
    Skövde is a town in south-central Sweden that serves as a major military hub and training center for the Swedish Army.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd592115fc8190b1aee1d8bbaf1ee3 completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69becf8f926481908f6e1cf33fc79a04 completed March 21, 2026, 5:04 p.m.
Created at: March 20, 2026, 1:11 p.m.