Triple

T12860904
Position Surface form Disambiguated ID Type / Status
Subject The Hustle E307583 entity
Predicate hasScreenwriter P62466 FINISHED
Object Paul Henning E330769 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 Henning | Statement: [The Hustle, hasScreenwriter, Paul Henning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Henning
Context triple: [The Hustle, hasScreenwriter, Paul Henning]
  • A. Paul Henning chosen
    Paul Henning was an American television and film writer-producer best known for creating the classic sitcom "The Beverly Hillbillies" and shaping 1960s rural comedy on TV.
  • B. George Hansen
    George Hansen is a fictional character from the 1958 Western film "Terror in a Texas Town."
  • C. Lloyd Hansen
    Lloyd Hansen is the ruthless and unhinged former CIA operative who serves as the primary villain in the action thriller film "The Gray Man."
  • D. Joseph Flummerfelt
    Joseph Flummerfelt was an acclaimed American choral conductor and educator, best known for his long association with the Westminster Choir and major orchestras and festivals around the world.
  • E. Larry Bryggman
    Larry Bryggman is an American actor best known for his long-running role on the soap opera "As the World Turns" and various film and television appearances.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708ba74881909b16c1e2ef5115db completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaca8958819086df70db2ba497a5 completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 5:37 p.m.