Triple

T6581150
Position Surface form Disambiguated ID Type / Status
Subject Riksmålsforbundet E157298 entity
Predicate awards P11 FINISHED
Object Lytterprisen
Lytterprisen is a Norwegian language and broadcasting award presented by Riksmålsforbundet to honor exemplary use of the Norwegian language in radio and audio media.
E605231 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: Lytterprisen | Statement: [Riksmålsforbundet, awards, Lytterprisen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lytterprisen
Context triple: [Riksmålsforbundet, awards, Lytterprisen]
  • A. The little Nobel
    The little Nobel is an informal nickname for the prestigious Nordic Prize, often seen as a regional counterpart to the Nobel Prize.
  • B. Tivoli Friheden
    Tivoli Friheden is an amusement park and recreational attraction located in Aarhus, Denmark.
  • C. The Winner
    The Winner is a suspense thriller novel by David Baldacci about a young woman entangled in a deadly conspiracy after being offered a rigged lottery win.
  • D. Vinderen
    Vinderen is a residential neighborhood in Oslo, Norway, known for its affluent character, green surroundings, and convenient access to the city center.
  • E. Løten
    Løten is a rural municipality in Innlandet county, Norway, known for its agricultural landscape and historic connections to painter Edvard Munch.
  • 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: Lytterprisen
Triple: [Riksmålsforbundet, awards, Lytterprisen]
Generated description
Lytterprisen is a Norwegian language and broadcasting award presented by Riksmålsforbundet to honor exemplary use of the Norwegian language in radio and audio media.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lytterprisen
Target entity description: Lytterprisen is a Norwegian language and broadcasting award presented by Riksmålsforbundet to honor exemplary use of the Norwegian language in radio and audio media.
  • A. The little Nobel
    The little Nobel is an informal nickname for the prestigious Nordic Prize, often seen as a regional counterpart to the Nobel Prize.
  • B. Sonningprisen
    Sonningprisen is a prestigious Danish award given biennially to individuals who have made outstanding contributions to European culture.
  • C. Tivoli Friheden
    Tivoli Friheden is an amusement park and recreational attraction located in Aarhus, Denmark.
  • D. The Winner
    The Winner is a suspense thriller novel by David Baldacci about a young woman entangled in a deadly conspiracy after being offered a rigged lottery win.
  • E. Vinderen
    Vinderen is a residential neighborhood in Oslo, Norway, known for its affluent character, green surroundings, and convenient access to the city center.
  • 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_69c6882b3a108190b3a9eb343ae4162c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae90c1b081908f851bff1dd19855 completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d572c4708190844f4b1abee8ca86 completed March 27, 2026, 7:07 p.m.
NEDg Description generation batch_69c6d9817b708190a3a66d40996cf2a1 completed March 27, 2026, 7:24 p.m.
NED2 Entity disambiguation (via description) batch_69c6daaa4be88190a07823df9427d2d5 completed March 27, 2026, 7:29 p.m.
Created at: March 27, 2026, 1:54 p.m.