Triple

T9447405
Position Surface form Disambiguated ID Type / Status
Subject Terminator: Dark Fate E227797 entity
Predicate editedBy P1954 FINISHED
Object Josh Schaeffer E314009 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: Josh Schaeffer | Statement: [Terminator: Dark Fate, editedBy, Josh Schaeffer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Josh Schaeffer
Context triple: [Terminator: Dark Fate, editedBy, Josh Schaeffer]
  • A. Josh Schaeffer chosen
    Josh Schaeffer is a film editor known for his work on major studio features, including the monster crossover blockbuster "Godzilla vs. Kong."
  • B. Jake Schreier
    Jake Schreier is an American film and music video director known for movies such as "Paper Towns" and "Robot & Frank."
  • C. Ken Schretzmann
    Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
  • D. Josh Sborz
    Josh Sborz is an American professional baseball pitcher known for his standout collegiate career at the University of Virginia, where he helped lead the Cavaliers to a national championship.
  • E. Jason Sehorn
    Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
  • 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f35394c8190aa77528dabd6139c completed April 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2e4d5f5008190a897b3b10b172592 completed April 5, 2026, 10:40 p.m.
Created at: March 30, 2026, 7:51 p.m.