Triple

T16456998
Position Surface form Disambiguated ID Type / Status
Subject Pay It Forward E399708 entity
Predicate producer P490 FINISHED
Object Steven Reuther E542156 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: Steven Reuther | Statement: [Pay It Forward, producer, Steven Reuther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steven Reuther
Context triple: [Pay It Forward, producer, Steven Reuther]
  • A. Steven Reuther chosen
    Steven Reuther was an American film producer known for his work on major Hollywood movies such as "Pretty Woman" and other commercially successful dramas and thrillers.
  • B. Andrew Meyer
    Andrew Meyer is a fictional character in the television series "Veep," known as the ex-husband of main character Selina Meyer and the father of her daughter Catherine.
  • C. Roy Reuther
    Roy Reuther was an influential American labor leader and United Auto Workers organizer who played a key role in building industrial unionism in the U.S. auto industry.
  • D. David Boggs
    David Boggs was an American electrical engineer and computer scientist best known as the co-inventor of Ethernet networking technology at Xerox PARC.
  • E. Jean Peters
    Jean Peters was an American film actress best known for her leading roles in 1940s and 1950s Hollywood adventure and drama films.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7dfd188190b03e9b4151a4d3d8 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f5015a881908447b64b699feb1a completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.