Triple

T4688900
Position Surface form Disambiguated ID Type / Status
Subject Eastern Sweden E103986 entity
Predicate contains P35 FINISHED
Object Västerås E366617 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: Västerås | Statement: [Eastern Sweden, contains, Västerås]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Västerås
Context triple: [Eastern Sweden, contains, Västerås]
  • A. Västerås chosen
    Västerås is a historic city in central Sweden known for its medieval cathedral, lakeside location on Lake Mälaren, and role as an important industrial and commercial center.
  • B. Södertälje
    Södertälje is a Swedish city southwest of Stockholm known for its industrial heritage, diverse population, and strategic location linking Lake Mälaren with the Baltic Sea via the Södertälje Canal.
  • C. 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.
  • 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. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • 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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6399621881909aa8ffb1c27284e9 completed March 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf9f5291f881909d9470a728667346 completed March 22, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:16 p.m.