Triple

T16697857
Position Surface form Disambiguated ID Type / Status
Subject High Wall E405762 entity
Predicate cinematographyBy 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: [High Wall, cinematographyBy, Paul Vogel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Vogel
Context triple: [High Wall, cinematographyBy, 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. Sam Koppelman
    Sam Koppelman is an American writer and political speechwriter known for co-authoring books with figures like Beto O’Rourke and for his work on voting rights and democracy.
  • D. 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."
  • E. David Dorfman
    David Dorfman is an American actor best known for playing the young boy Aidan Keller in the horror film "The Ring" and its sequel.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3832e93c48190a594c498e9cc901a completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00919ee61c81909928dd26270e9614 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:19 a.m.