Triple

T2686949
Position Surface form Disambiguated ID Type / Status
Subject Cavalier Johnson E57505 entity
Predicate givenName P17 FINISHED
Object Cavalier
Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
 E288656 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: Cavalier | Statement: [Cavalier Johnson, givenName, Cavalier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cavalier
Context triple: [Cavalier Johnson, givenName, Cavalier]
  • A. Cavalier
    Cavalier is the costumed mascot character representing the University of Virginia’s athletic teams, typically depicted as a historical Virginia cavalryman.
  • B. Bassett
    Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
  • C. Chester French
    Chester French is an American indie pop duo known for their genre-blending sound, witty lyrics, and early association with producers like Pharrell Williams.
  • D. Prancer
    Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
  • E. Landseer
    Landseer is the middle name of renowned British architect Sir Edwin Lutyens, best known for his influential country houses and war memorial designs.
  • 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: Cavalier
Triple: [Cavalier Johnson, givenName, Cavalier]
Generated description
Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cavalier
Target entity description: Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
  • A. Cavalier
    Cavalier is the costumed mascot character representing the University of Virginia’s athletic teams, typically depicted as a historical Virginia cavalryman.
  • B. Bassett
    Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
  • C. Chester French
    Chester French is an American indie pop duo known for their genre-blending sound, witty lyrics, and early association with producers like Pharrell Williams.
  • D. Prancer
    Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
  • E. Landseer
    Landseer is the middle name of renowned British architect Sir Edwin Lutyens, best known for his influential country houses and war memorial designs.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9f080108190ab662a3a064cb5a9 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa07228088190bb4942b3a25c938b completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa0ff9c10819096d06ead6dc87d04 completed March 10, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69afa1e4ffb08190a6d96665ee566ea7 completed March 10, 2026, 4:45 a.m.
Created at: March 6, 2026, 9:54 p.m.