Triple

T16037600
Position Surface form Disambiguated ID Type / Status
Subject Astrid Lindgren E389008 entity
Predicate placeOfBirth P1 FINISHED
Object Vimmerby
Vimmerby is a small town in southern Sweden best known as the birthplace of beloved children's author Astrid Lindgren and for its associated literary tourism.
 E1248148 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: Vimmerby | Statement: [Astrid Lindgren, placeOfBirth, Vimmerby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vimmerby
Context triple: [Astrid Lindgren, placeOfBirth, Vimmerby]
  • A. Söderhamn
    Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
  • B. Hässleholm
    Hässleholm is a town in southern Sweden’s Skåne County known as a regional railway hub and service center.
  • C. Ronneby
    Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
  • D. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • E. Hammarö
    Hammarö is a Swedish island and municipality in Värmland County, known for its forests, coastline, and proximity to the city of Karlstad.
  • 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: Vimmerby
Triple: [Astrid Lindgren, placeOfBirth, Vimmerby]
Generated description
Vimmerby is a small town in southern Sweden best known as the birthplace of beloved children's author Astrid Lindgren and for its associated literary tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vimmerby
Target entity description: Vimmerby is a small town in southern Sweden best known as the birthplace of beloved children's author Astrid Lindgren and for its associated literary tourism.
  • A. Söderhamn
    Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
  • B. Hässleholm
    Hässleholm is a town in southern Sweden’s Skåne County known as a regional railway hub and service center.
  • C. Ronneby
    Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
  • D. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • E. Hammarö
    Hammarö is a Swedish island and municipality in Värmland County, known for its forests, coastline, and proximity to the city of Karlstad.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1833da68881908710fb2c28e8c6d0 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01232399008190b23dfaec237563ef completed May 11, 2026, 12:30 a.m.
NEDg Description generation batch_6a0124ce490c81909d5cfd86b7dabb71 completed May 11, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a012569322081908b60694851d50e4b completed May 11, 2026, 12:40 a.m.
Created at: April 10, 2026, 4:56 a.m.