Triple

T15092089
Position Surface form Disambiguated ID Type / Status
Subject Skaraborg County E360443 entity
Predicate contains P35 FINISHED
Object Götene
Götene is a small locality and municipality in western Sweden known for its rural landscape and proximity to the historic Kinnekulle plateau by Lake Vänern.
E1138166 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: Götene | Statement: [Skaraborg County, contains, Götene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Götene
Context triple: [Skaraborg County, contains, Götene]
  • A. Arboga
    Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
  • B. Gislaved
    Gislaved is a tire brand known for producing reliable winter and all-season tires, particularly popular in Northern and Central Europe.
  • C. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • D. Hudiksvall
    Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
  • E. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • 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: Götene
Triple: [Skaraborg County, contains, Götene]
Generated description
Götene is a small locality and municipality in western Sweden known for its rural landscape and proximity to the historic Kinnekulle plateau by Lake Vänern.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Götene
Target entity description: Götene is a small locality and municipality in western Sweden known for its rural landscape and proximity to the historic Kinnekulle plateau by Lake Vänern.
  • A. Arboga
    Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
  • B. Gislaved
    Gislaved is a tire brand known for producing reliable winter and all-season tires, particularly popular in Northern and Central Europe.
  • C. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • D. Hudiksvall
    Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
  • E. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • 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_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_69feb7e47b20819084145008474f47b7 completed May 9, 2026, 4:28 a.m.
NEDg Description generation batch_69feb9abd8588190bcf43f9974429c4d completed May 9, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69feba30cc748190bc0141b205f7e91b completed May 9, 2026, 4:38 a.m.
Created at: April 10, 2026, 3:04 a.m.