Triple

T16329463
Position Surface form Disambiguated ID Type / Status
Subject Agneta E396509 entity
Predicate hasNotableBearer P458 FINISHED
Object Agneta Andersson
Agneta Andersson is a Swedish sprint canoer and multiple Olympic gold medalist who was one of the sport’s leading competitors in the 1980s and early 1990s.
E1210915 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: Agneta Andersson | Statement: [Agneta, hasNotableBearer, Agneta Andersson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agneta Andersson
Context triple: [Agneta, hasNotableBearer, Agneta Andersson]
  • A. Agneta Eckemyr
    Agneta Eckemyr was a Swedish actress and model known for her work in European cinema and appearances in international fashion magazines during the 1970s and 1980s.
  • B. Agneta Åse Fältskog
    Agneta Åse Fältskog is a Swedish singer, songwriter, and member of the internationally renowned pop group ABBA.
  • C. Agneta Ekmanner
    Agneta Ekmanner is a Swedish actress known for her work in film and television, and for having been married to renowned tenor Nicolai Gedda.
  • D. Margareta Wästberg
    Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
  • E. Ulla Andersson
    Ulla Andersson is a Swedish model best known for her marriage to legendary music producer Quincy Jones in the 1960s.
  • 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: Agneta Andersson
Triple: [Agneta, hasNotableBearer, Agneta Andersson]
Generated description
Agneta Andersson is a Swedish sprint canoer and multiple Olympic gold medalist who was one of the sport’s leading competitors in the 1980s and early 1990s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Agneta Andersson
Target entity description: Agneta Andersson is a Swedish sprint canoer and multiple Olympic gold medalist who was one of the sport’s leading competitors in the 1980s and early 1990s.
  • A. Agneta Eckemyr
    Agneta Eckemyr was a Swedish actress and model known for her work in European cinema and appearances in international fashion magazines during the 1970s and 1980s.
  • B. Agneta Åse Fältskog
    Agneta Åse Fältskog is a Swedish singer, songwriter, and member of the internationally renowned pop group ABBA.
  • C. Agneta Ekmanner
    Agneta Ekmanner is a Swedish actress known for her work in film and television, and for having been married to renowned tenor Nicolai Gedda.
  • D. Margareta Wästberg
    Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
  • E. Ulla Andersson
    Ulla Andersson is a Swedish model best known for her marriage to legendary music producer Quincy Jones in the 1960s.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4ddc5608190b24fe2e871691470 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a003556630081909e60e378e97b06fb completed May 10, 2026, 7:35 a.m.
NEDg Description generation batch_6a0036e07d2081908db03dcc133f8421 completed May 10, 2026, 7:42 a.m.
NED2 Entity disambiguation (via description) batch_6a00384f51d081909a5ab0630f82d173 completed May 10, 2026, 7:48 a.m.
Created at: April 10, 2026, 5:07 a.m.