Triple

T8871492
Position Surface form Disambiguated ID Type / Status
Subject Ljusdal Municipality E211166 entity
Predicate seat P75 FINISHED
Object Ljusdal
Ljusdal is a locality in Gävleborg County, Sweden, known as a regional center in the historical province of Hälsingland.
E211166 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: Ljusdal | Statement: [Ljusdal Municipality, seat, Ljusdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ljusdal
Context triple: [Ljusdal Municipality, seat, Ljusdal]
  • A. Ljusdal Municipality
    Ljusdal Municipality is a local government area in central Sweden known for its forests, rivers, and rural communities within Gävleborg County.
  • B. Nässjö
    Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
  • C. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • D. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • E. Molndal
    Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
  • 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: Ljusdal
Triple: [Ljusdal Municipality, seat, Ljusdal]
Generated description
Ljusdal is a locality in Gävleborg County, Sweden, known as a regional center in the historical province of Hälsingland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ljusdal
Target entity description: Ljusdal is a locality in Gävleborg County, Sweden, known as a regional center in the historical province of Hälsingland.
  • A. Ljusdal Municipality chosen
    Ljusdal Municipality is a local government area in central Sweden known for its forests, rivers, and rural communities within Gävleborg County.
  • B. Nässjö
    Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
  • C. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • D. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • E. Molndal
    Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
  • F. None of above.

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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61281e888190a32b08980310979f completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0f1f1888190a5b514b895e44799 completed April 3, 2026, 11:13 a.m.
NEDg Description generation batch_69cfa1ee350881909355371d824ebe3d completed April 3, 2026, 11:18 a.m.
NED2 Entity disambiguation (via description) batch_69cfa26ab1b881909e42a435f4e3333c completed April 3, 2026, 11:20 a.m.
Created at: March 30, 2026, 6:51 p.m.