Triple

T6135050
Position Surface form Disambiguated ID Type / Status
Subject Battleground E136812 entity
Predicate cinematographer P1953 FINISHED
Object Paul Vogel E25375 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: Paul Vogel | Statement: [Battleground, cinematographer, Paul Vogel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Vogel
Context triple: [Battleground, cinematographer, Paul Vogel]
  • A. Paul Vogel chosen
    Paul Vogel was an American cinematographer best known for his work on classic Hollywood films, including the Oscar-winning "Battleground."
  • B. Gene Shue
    Gene Shue was an American professional basketball player and longtime NBA head coach known for revitalizing struggling franchises and leading multiple teams deep into the playoffs.
  • C. Bruce Weitz
    Bruce Weitz is an American actor best known for his Emmy-winning role as the eccentric detective Mick Belker on the television series "Hill Street Blues."
  • D. Philip Dunne
    Philip Dunne was an American screenwriter, director, and producer best known for his work on classic Hollywood films from the 1930s through the 1960s.
  • E. Michael-Leon Wooley
    Michael-Leon Wooley is an American actor and voice actor best known for his rich baritone performances in film, television, and theater, including prominent roles in animated features and Broadway productions.
  • 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_69c008a179388190a3b5a081bbf46d55 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c80a6088190a028967b682fed2b completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1416e8fa8819092bf830cbaa56647 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:15 p.m.