Triple

T8097301
Position Surface form Disambiguated ID Type / Status
Subject Manuel Buckner E189017 entity
Predicate name P16 FINISHED
Object Manuel Buckner E189017 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: Manuel Buckner | Statement: [Manuel Buckner, name, Manuel Buckner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manuel Buckner
Context triple: [Manuel Buckner, name, Manuel Buckner]
  • A. Manuel Buckner chosen
    Manuel Buckner is an individual notable enough to be specifically cited as a bearer of the surname Buckner.
  • B. Robert Buckner
    Robert Buckner was an American screenwriter and film producer known for his work on classic Hollywood films in the 1930s and 1940s.
  • C. Rufus Buckner
    Rufus Buckner is an individual notable enough to be recognized as a prominent bearer of the Buckner surname.
  • D. Branford Buckner
    Branford Buckner is a former American football defensive tackle who played in the NFL and later became a defensive line coach.
  • E. Hannibal Brooks
    Hannibal Brooks is a 1969 British war comedy film about a prisoner of war who escapes through the Alps with an elephant, directed by Michael Winner and starring Oliver Reed.
  • 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_69ca82b886d88190a9cba0d5a4a27521 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429319048190b612c8060a9a24d2 completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc641a4b4881908a1aec4bc2ed619e completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:30 p.m.