Triple

T14173612
Position Surface form Disambiguated ID Type / Status
Subject Secret Window E351274 entity
Predicate character P662 FINISHED
Object Mort Rainey E1083541 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: Mort Rainey | Statement: [Secret Window, character, Mort Rainey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mort Rainey
Context triple: [Secret Window, character, Mort Rainey]
  • A. Mort Rainey chosen
    Mort Rainey is a troubled, reclusive writer whose unraveling sanity drives the psychological horror at the center of Stephen King’s novella and its film adaptation "Secret Window."
  • B. Cliff Barker
    Cliff Barker was an American professional basketball player best known for his time as a guard with the Indianapolis Olympians in the early years of the NBA.
  • C. Johnny Castle
    Johnny Castle is the charismatic dance instructor and romantic lead portrayed by Patrick Swayze in the 1987 film "Dirty Dancing."
  • D. Don Harvey
    Don Harvey is an American character actor known for his intense supporting roles in films such as the Vietnam War drama "Casualties of War."
  • E. Marty South
    Marty South is a quiet, self-sacrificing young woman in Thomas Hardy’s novel "The Woodlanders," known for her unrequited love and deep connection to the rural woodland setting.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b7cc3081909f4fa371e1eae130 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd193f85e88190b37a37747ec9d019 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:01 a.m.