Triple

T15092078
Position Surface form Disambiguated ID Type / Status
Subject Skaraborg County E360443 entity
Predicate contains P35 FINISHED
Object Skövde E275769 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: Skövde | Statement: [Skaraborg County, contains, Skövde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skövde
Context triple: [Skaraborg County, contains, Skövde]
  • A. Skövde chosen
    Skövde is a town in south-central Sweden that serves as a major military hub and training center for the Swedish Army.
  • B. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • C. Växjö
    Växjö is a city in southern Sweden known for its lakeside setting, environmental sustainability initiatives, and role as a regional cultural and educational center.
  • D. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • E. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027925788190b955fdc6626adf7d completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbb7b1e48190b55c40e0cb837446 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 3:04 a.m.