Triple

T18888403
Position Surface form Disambiguated ID Type / Status
Subject Big Man on Campus E462017 entity
Predicate editor P1954 FINISHED
Object Patrick Kennedy NE NERFINISHED

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: Patrick Kennedy | Statement: [Big Man on Campus, editor, Patrick Kennedy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patrick Kennedy
Context triple: [Big Man on Campus, editor, Patrick Kennedy]
  • A. Patrick Kennedy
    Patrick Kennedy is an American competitive swimmer known for training with the prestigious North Baltimore Aquatic Club.
  • B. Patrick Kennedy chosen
    Patrick Kennedy is an editor known for his work on the publication "Tap."
  • C. Patrick Kennedy
    Patrick Kennedy is a British actor known for his work in film and television, including prominent roles in period dramas and literary adaptations.
  • D. Patrick Joseph Kennedy
    Patrick Joseph Kennedy was an American businessman and politician who served in the Massachusetts state legislature and was a prominent patriarch of the Kennedy political family.
  • E. Patrick J. Kennedy Sr.
    Patrick J. Kennedy Sr. was an American politician from Massachusetts and a member of the influential Kennedy family.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c478d8c481909291e7c471e5095a completed April 20, 2026, 6:15 a.m.
Created at: April 10, 2026, 11:58 a.m.