Triple

T7044293
Position Surface form Disambiguated ID Type / Status
Subject Deuces Wild E163591 entity
Predicate producer P490 FINISHED
Object Frank Sacks E163591 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: Frank Sacks | Statement: [Deuces Wild, producer, Frank Sacks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Sacks
Context triple: [Deuces Wild, producer, Frank Sacks]
  • A. Frank Sacks chosen
    Frank Sacks is a film producer best known for his work on the crime drama movie "Deuces Wild."
  • B. Jerome Sacks
    Jerome Sacks is an American statistician known for his contributions to experimental design, statistical theory, and the development of computer experiments.
  • C. Stephen H. Sachs
    Stephen H. Sachs is an American lawyer and politician who served as Maryland’s attorney general and was known for his work on legal reform and civil rights.
  • D. Michael Sacks
    Michael Sacks is an American actor best known for his role as Billy Pilgrim in the film adaptation of Kurt Vonnegut’s "Slaughterhouse-Five."
  • E. Michael A. Gottlieb
    Michael A. Gottlieb is a physicist and editor known for his work on Richard Feynman–related educational materials, including co-editing "Feynman’s Tips on Physics."
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e23730888190a827ca5c61c4eed0 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7887799f48190b4fa311defd8e9fd completed March 28, 2026, 7:51 a.m.
Created at: March 27, 2026, 2:37 p.m.