Triple

T5475711
Position Surface form Disambiguated ID Type / Status
Subject Stakeout E122946 entity
Predicate editedBy P1954 FINISHED
Object Tom Rolf E214378 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 Rolf | Statement: [Stakeout, editedBy, Tom Rolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Rolf
Context triple: [Stakeout, editedBy, Tom Rolf]
  • A. Tom Rolf chosen
    Tom Rolf was an American film editor best known for his work on acclaimed movies such as "Taxi Driver" and for winning an Academy Award for editing "The Right Stuff."
  • B. Ron Hagen
    Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
  • C. Duane Schuler
    Duane Schuler is an American theatrical lighting designer known for his work in opera, including major productions at leading opera houses.
  • D. Curt Rothenberger
    Curt Rothenberger was a German jurist and high-ranking Nazi official who played a key role in implementing and justifying the Third Reich’s oppressive legal policies.
  • E. Bill Elfers
    Bill Elfers was an American venture capitalist best known for co-founding the influential Silicon Valley and Boston-based firm Greylock Partners.
  • 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_69bd46459ff48190823377457bcf7128 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd923465c88190ad9c1b75b268f7ca completed March 20, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf489a8f9881908aec81e59ed1e3e4 completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:09 p.m.