Triple

T5338759
Position Surface form Disambiguated ID Type / Status
Subject Vibeke Brahe E123891 entity
Predicate givenName P17 FINISHED
Object Vibeke
Vibeke is a Scandinavian feminine given name of Old Norse origin, traditionally used in Denmark and Norway.
E511291 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: Vibeke | Statement: [Vibeke Brahe, givenName, Vibeke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vibeke
Context triple: [Vibeke Brahe, givenName, Vibeke]
  • A. Birgitte
    Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
  • B. Ingeborg
    Ingeborg is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • C. Kristina Tholstrup
    Kristina Tholstrup is a Swedish socialite best known as the widow of James Bond actor Sir Roger Moore.
  • D. Rebekka Vaark
    Rebekka Vaark is a central character in Toni Morrison’s novel "A Mercy," depicted as a European immigrant wife navigating hardship, loss, and the complexities of early American colonial life on a remote farm.
  • E. Astrid
    Astrid is a Belgian princess and member of the country’s royal family.
  • 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: Vibeke
Triple: [Vibeke Brahe, givenName, Vibeke]
Generated description
Vibeke is a Scandinavian feminine given name of Old Norse origin, traditionally used in Denmark and Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vibeke
Target entity description: Vibeke is a Scandinavian feminine given name of Old Norse origin, traditionally used in Denmark and Norway.
  • A. Birgitte
    Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
  • B. Ingeborg
    Ingeborg is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • C. Kristina Tholstrup
    Kristina Tholstrup is a Swedish socialite best known as the widow of James Bond actor Sir Roger Moore.
  • D. Rebekka Vaark
    Rebekka Vaark is a central character in Toni Morrison’s novel "A Mercy," depicted as a European immigrant wife navigating hardship, loss, and the complexities of early American colonial life on a remote farm.
  • E. Astrid
    Astrid is a Belgian princess and member of the country’s royal family.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c8415c819099a0b26e07360f01 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c54ca4819095ca1d81ee061937 completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf197733b48190910bdd60fbd94fff completed March 21, 2026, 10:19 p.m.
NED2 Entity disambiguation (via description) batch_69bf19e2d1fc81909030e32bb18d46dc completed March 21, 2026, 10:21 p.m.
Created at: March 20, 2026, 2 p.m.