Triple

T14396200
Position Surface form Disambiguated ID Type / Status
Subject Mikkel Svane E356954 entity
Predicate givenName P17 FINISHED
Object Mikkel
Mikkel is a Scandinavian male given name commonly used in Denmark and Norway, equivalent to Michael in English.
 E99056 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: Mikkel | Statement: [Mikkel Svane, givenName, Mikkel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mikkel
Context triple: [Mikkel Svane, givenName, Mikkel]
  • A. Mads
    Mads is a Scandinavian given name commonly used for males, particularly in Denmark and Norway.
  • B. Mads Dittmann Mikkelsen
    Mads Dittmann Mikkelsen is a Danish actor renowned for his versatile performances in films and television series such as "Casino Royale," "Hannibal," and "Another Round."
  • C. Mikkel Kessler
    Mikkel Kessler is a Danish former professional boxer and multiple-time super middleweight world champion known for his technical skill and powerful jab.
  • D. Mikael
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • E. Jørgen
    Jørgen is a Scandinavian male given name, commonly used in Denmark and Norway and related to the name George.
  • 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: Mikkel
Triple: [Mikkel Svane, givenName, Mikkel]
Generated description
Mikkel is a Scandinavian male given name commonly used in Denmark and Norway, equivalent to Michael in English.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mikkel
Target entity description: Mikkel is a Scandinavian male given name commonly used in Denmark and Norway, equivalent to Michael in English.
  • A. Mads
    Mads is a Scandinavian given name commonly used for males, particularly in Denmark and Norway.
  • B. Mads Dittmann Mikkelsen
    Mads Dittmann Mikkelsen is a Danish actor renowned for his versatile performances in films and television series such as "Casino Royale," "Hannibal," and "Another Round."
  • C. Mikkel Kessler
    Mikkel Kessler is a Danish former professional boxer and multiple-time super middleweight world champion known for his technical skill and powerful jab.
  • D. Mikael chosen
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • E. Jørgen
    Jørgen is a Scandinavian male given name, commonly used in Denmark and Norway and related to the name George.
  • F. None of above.

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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90826f908190b3969af9b7cf922f completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd551cbdb08190a9ea53e607f2555b completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd55d90ed08190b6a0184715f39ff4 completed May 8, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_69fd565d32fc8190acc1e733537a23cb completed May 8, 2026, 3:19 a.m.
Created at: April 10, 2026, 1:17 a.m.