Triple

T8449324
Position Surface form Disambiguated ID Type / Status
Subject Four Rooms E199761 entity
Predicate editingBy P1954 FINISHED
Object Brad Wilhite E310036 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: Brad Wilhite | Statement: [Four Rooms, editingBy, Brad Wilhite]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brad Wilhite
Context triple: [Four Rooms, editingBy, Brad Wilhite]
  • A. Brad Wilhite chosen
    Brad Wilhite is a film editor known for his work on major studio comedies, including the holiday sequel "Daddy's Home 2."
  • B. Mark Wohlers
    Mark Wohlers is a former Major League Baseball relief pitcher best known as the hard-throwing closer for the Atlanta Braves during the mid-1990s.
  • C. Frank Lanning
    Frank Lanning was an American character actor of the silent film era, known for his supporting roles in numerous Westerns and early Hollywood productions.
  • D. Steve Symms
    Steve Symms is a Republican politician who represented Idaho in the U.S. Senate during the 1980s and early 1990s.
  • E. Pat Proft
    Pat Proft is an American comedy writer and screenwriter best known for his work on spoof film franchises such as The Naked Gun and Police Academy.
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe445b7988190b53ae45070c70d1d completed March 31, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dc85e48819083340d022d0dba9b completed April 2, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:09 p.m.