Triple

T14881733
Position Surface form Disambiguated ID Type / Status
Subject Värmland County E350015 entity
Predicate hasCity P316 FINISHED
Object Arvika
Arvika is a small Swedish town known for its lakeside setting, cultural events, and role as a local industrial and commercial center in western Sweden.
E1125722 NE FINISHED

How this triple was built (4 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: Arvika | Statement: [Värmland County, hasCity, Arvika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arvika
Context triple: [Värmland County, hasCity, Arvika]
  • A. Arvidsjaur
    Arvidsjaur is a small town in northern Sweden known for its military presence, winter testing facilities, and proximity to Arctic wilderness.
  • B. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • C. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • D. Arbrå
    Arbrå is a small locality in Gävleborg County, Sweden, known as the birthplace of actor Peter Stormare.
  • E. Kungälv
    Kungälv is a town in western Sweden known for the historic Bohus Fortress and its location near the Göta älv north of Gothenburg.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Arvika
Triple: [Värmland County, hasCity, Arvika]
Generated description
Arvika is a small Swedish town known for its lakeside setting, cultural events, and role as a local industrial and commercial center in western Sweden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arvika
Target entity description: Arvika is a small Swedish town known for its lakeside setting, cultural events, and role as a local industrial and commercial center in western Sweden.
  • A. Arvidsjaur
    Arvidsjaur is a small town in northern Sweden known for its military presence, winter testing facilities, and proximity to Arctic wilderness.
  • B. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • C. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • D. Arbrå
    Arbrå is a small locality in Gävleborg County, Sweden, known as the birthplace of actor Peter Stormare.
  • E. Kungälv
    Kungälv is a town in western Sweden known for the historic Bohus Fortress and its location near the Göta älv north of Gothenburg.
  • F. None of above. chosen

Provenance (5 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e7c0e48190af2d68a71130585c completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b591f3c81909ea8a9217d96e0d2 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6c55d6b88190b0f57009be962194 completed May 8, 2026, 11:05 p.m.
NED2 Entity disambiguation (via description) batch_69fe6e56e7e88190b70497e168d707de completed May 8, 2026, 11:14 p.m.
Created at: April 10, 2026, 1:56 a.m.