Triple

T14520312
Position Surface form Disambiguated ID Type / Status
Subject Hereafter E340631 entity
Predicate cinematographer P1953 FINISHED
Object Tom Stern E203049 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: Tom Stern | Statement: [Hereafter, cinematographer, Tom Stern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Stern
Context triple: [Hereafter, cinematographer, Tom Stern]
  • A. Tom Stern chosen
    Tom Stern is an American cinematographer best known for his frequent collaborations with director Clint Eastwood on numerous acclaimed films.
  • B. Jonathan Stern
    Jonathan Stern is an American film and television producer best known for his work on offbeat comedies such as "Wet Hot American Summer" and various projects for Adult Swim and streaming platforms.
  • C. Ben Schulberg
    Ben Schulberg was an American film producer and studio executive active during the early Hollywood era.
  • D. Mike Kellerman
    Mike Kellerman is a fictional Baltimore homicide detective known for his morally complex investigations and personal struggles on the television series "Homicide: Life on the Street."
  • E. Mike Nussbaum
    Mike Nussbaum is an American actor and director known for his character roles in film, television, and theater, including work in David Mamet projects such as "House of Games."
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a70b15c81908773633e989ef704 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab07e08819085a6a21cc9cea1fa completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:22 a.m.