Triple

T15751936
Position Surface form Disambiguated ID Type / Status
Subject Tower Heist E381867 entity
Predicate screenwriter P2831 FINISHED
Object Jeff Nathanson E318412 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: Jeff Nathanson | Statement: [Tower Heist, screenwriter, Jeff Nathanson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Nathanson
Context triple: [Tower Heist, screenwriter, Jeff Nathanson]
  • A. Jeff Nathanson chosen
    Jeff Nathanson is an American screenwriter and film director best known for writing high-profile Hollywood films such as "Catch Me If You Can," "The Terminal," and Disney's live-action "The Lion King."
  • B. Michael Nathanson
    Michael Nathanson is a film producer known for his work on major Hollywood movies, including the legal drama "A Time to Kill."
  • C. Brent Judd
    Brent Judd is a film and television producer best known for his work on the comedy series "Trainwreck."
  • D. Greg Latter
    Greg Latter is a screenwriter best known for his work on the apartheid-era drama film "Goodbye Bafana."
  • E. Mike Lilley
    Mike Lilley is known as the husband of American sports broadcaster and television personality Melissa Stark.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e05030e31081908c307a8dc7067db4 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00580789c08190994c5c71525aadc6 completed May 10, 2026, 10:03 a.m.
Created at: April 10, 2026, 4:47 a.m.