Triple

T9738875
Position Surface form Disambiguated ID Type / Status
Subject Captain America: The Winter Soldier E236134 entity
Predicate editor P1954 FINISHED
Object Matthew Schmidt E239842 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: Matthew Schmidt | Statement: [Captain America: The Winter Soldier, editor, Matthew Schmidt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Schmidt
Context triple: [Captain America: The Winter Soldier, editor, Matthew Schmidt]
  • A. Matthew Schmidt chosen
    Matthew Schmidt is a film editor best known for his work on major Marvel Cinematic Universe films, including Avengers: Infinity War.
  • B. Christopher Schmidt
    Christopher Schmidt is the real name of the DC Comics antihero Peacemaker, a vigilante obsessed with achieving peace through often extreme and violent means.
  • C. John Luessenhop
    John Luessenhop is an American film director and screenwriter best known for helming genre and action films, including the horror sequel "Texas Chainsaw 3D."
  • D. 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.
  • E. Matthew Jensen
    Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9ef43fec8190987628f401a27436 completed April 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d79445b9288190a684184285966fa8 completed April 9, 2026, 11:57 a.m.
Created at: March 30, 2026, 8:22 p.m.