Triple

T18413818
Position Surface form Disambiguated ID Type / Status
Subject Nora Municipality E441834 entity
Predicate contains P35 FINISHED
Object Gyttorp
Gyttorp is a locality in central Sweden known historically for its explosives industry and distinctive functionalist residential architecture.
 E1324354 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: Gyttorp | Statement: [Nora Municipality, contains, Gyttorp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gyttorp
Context triple: [Nora Municipality, contains, Gyttorp]
  • A. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • B. Stordal
    Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
  • C. Hägersten
    Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
  • D. Nannfeldt
    Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
  • E. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • 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: Gyttorp
Triple: [Nora Municipality, contains, Gyttorp]
Generated description
Gyttorp is a locality in central Sweden known historically for its explosives industry and distinctive functionalist residential architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gyttorp
Target entity description: Gyttorp is a locality in central Sweden known historically for its explosives industry and distinctive functionalist residential architecture.
  • A. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • B. Stordal
    Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
  • C. Hägersten
    Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
  • D. Nannfeldt
    Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
  • E. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a26d268819098e6791dc98efcda completed April 19, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03f0a40c7481909a226c2be0de8d9d completed May 13, 2026, 3:31 a.m.
NEDg Description generation batch_6a03fa81964481909f0049ad756d4755 completed May 13, 2026, 4:13 a.m.
NED2 Entity disambiguation (via description) batch_6a03fac766d88190afee2a6b540dc58e completed May 13, 2026, 4:15 a.m.
Created at: April 10, 2026, 10:47 a.m.