Triple

T7482728
Position Surface form Disambiguated ID Type / Status
Subject Göran Persson E176800 entity
Predicate placeOfBirth P1 FINISHED
Object Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
E671798 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: Vingåker | Statement: [Göran Persson, placeOfBirth, Vingåker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vingåker
Context triple: [Göran Persson, placeOfBirth, Vingåker]
  • A. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • B. Vågå
    Vågå is a rural municipality in Innlandet county, Norway, known for its traditional farming landscape, historic stave church, and proximity to the Jotunheimen mountain area.
  • C. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • D. Kungsbacka
    Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
  • E. Grebbestad
    Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
  • 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: Vingåker
Triple: [Göran Persson, placeOfBirth, Vingåker]
Generated description
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vingåker
Target entity description: Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
  • A. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • B. Vågå
    Vågå is a rural municipality in Innlandet county, Norway, known for its traditional farming landscape, historic stave church, and proximity to the Jotunheimen mountain area.
  • C. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • D. Kungsbacka
    Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
  • E. Grebbestad
    Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5374bb08190bdf6ca72a3d0cd1c completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84eed875c81908922057730834a84 completed March 28, 2026, 9:58 p.m.
NEDg Description generation batch_69c850d3fe2081909490aea1bc09faa3 completed March 28, 2026, 10:06 p.m.
NED2 Entity disambiguation (via description) batch_69c8512f548c8190b5120a58abefade7 completed March 28, 2026, 10:07 p.m.
Created at: March 27, 2026, 3:42 p.m.