Triple

T23301504
Position Surface form Disambiguated ID Type / Status
Subject Ragnar Skanåker E590315 entity
Predicate familyName P18 FINISHED
Object Skanåker
Skanåker is a Swedish surname most notably associated with Ragnar Skanåker, a renowned Olympic sport shooter.
 E1580275 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: Skanåker | Statement: [Ragnar Skanåker, familyName, Skanåker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Skanåker
Context triple: [Ragnar Skanåker, familyName, Skanåker]
  • A. Skanstull
    Skanstull is a district in southern central Stockholm, Sweden, known as a major traffic junction and gateway to the island of Södermalm.
  • B. Skanzen
    Skanzen is Hungary’s largest open-air ethnographic museum in Szentendre, showcasing traditional rural architecture, folk culture, and everyday life from various regions of the country.
  • C. Scaniarinken
    Scaniarinken is a multi-purpose indoor arena in Södertälje, Sweden, best known as the home venue for the ice hockey club Södertälje SK.
  • D. Skaun
    Skaun is a rural municipality in Trøndelag county, Norway, known for its scenic landscapes, agriculture, and proximity to the city of Trondheim.
  • E. Sköndal
    Sköndal is a residential district in southern Stockholm, Sweden, known for its green areas and proximity to lakes.
  • 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: Skanåker
Triple: [Ragnar Skanåker, familyName, Skanåker]
Generated description
Skanåker is a Swedish surname most notably associated with Ragnar Skanåker, a renowned Olympic sport shooter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Skanåker
Target entity description: Skanåker is a Swedish surname most notably associated with Ragnar Skanåker, a renowned Olympic sport shooter.
  • A. Skanstull
    Skanstull is a district in southern central Stockholm, Sweden, known as a major traffic junction and gateway to the island of Södermalm.
  • B. Skanzen
    Skanzen is Hungary’s largest open-air ethnographic museum in Szentendre, showcasing traditional rural architecture, folk culture, and everyday life from various regions of the country.
  • C. Scaniarinken
    Scaniarinken is a multi-purpose indoor arena in Södertälje, Sweden, best known as the home venue for the ice hockey club Södertälje SK.
  • D. Skaun
    Skaun is a rural municipality in Trøndelag county, Norway, known for its scenic landscapes, agriculture, and proximity to the city of Trondheim.
  • E. Sköndal
    Sköndal is a residential district in southern Stockholm, Sweden, known for its green areas and proximity to lakes.
  • 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_69e25d1c0ecc8190a355aa229f06d0e0 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f196d37fd08190ad2d199c54324c02 completed April 29, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4c9730908190960a47f7fee9e0c2 completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c4ee292f08190a44326d433f37c65 completed May 19, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0c4f796b688190a8971ebd238e08f2 completed May 19, 2026, 11:54 a.m.
Created at: April 17, 2026, 5:04 p.m.