Triple

T8243905
Position Surface form Disambiguated ID Type / Status
Subject Sometimes They Come Back E192802 entity
Predicate firstPublishedIn P309 FINISHED
Object Cavalier E721763 NE FINISHED

How this triple was built (2 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: [Sometimes They Come Back, firstPublishedIn, Cavalier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cavalier
Context triple: [Sometimes They Come Back, firstPublishedIn, 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. Cavalier
    Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
  • C. Cavalier chosen
    Cavalier was a mid-20th-century American men's magazine known for publishing fiction, including early works by notable authors such as Stephen King.
  • D. Bassett
    Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
  • E. Philander Chase
    Philander Chase was a 19th-century American Episcopal bishop and educator best known for establishing influential frontier colleges and promoting religious education in the Midwest.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78711f5081909c2f357334491a07 completed March 31, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd680b0f608190b69336228346b47d completed April 1, 2026, 6:46 p.m.
Created at: March 30, 2026, 5:47 p.m.