Triple

T3145537
Position Surface form Disambiguated ID Type / Status
Subject Västra Götaland County E65754 entity
Predicate contains P35 FINISHED
Object Vänersborg
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
E331595 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: Vänersborg | Statement: [Västra Götaland County, contains, Vänersborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vänersborg
Context triple: [Västra Götaland County, contains, Vänersborg]
  • A. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • B. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • C. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Västerhaninge
    Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
  • 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: Vänersborg
Triple: [Västra Götaland County, contains, Vänersborg]
Generated description
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vänersborg
Target entity description: Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
  • A. Strängnäs
    Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
  • B. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • C. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • D. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • E. Västerhaninge
    Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59797788190a8d71262888c5df0 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224f18e80819083be53c556d56947 completed March 12, 2026, 2:29 a.m.
NEDg Description generation batch_69b2271961048190906b6fa25e4b560c completed March 12, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_69b227becba08190b5e4b3dae277ce51 completed March 12, 2026, 2:41 a.m.
Created at: March 8, 2026, 3:05 p.m.