Triple

T15496459
Position Surface form Disambiguated ID Type / Status
Subject The Craft E378829 entity
Predicate castMember P1668 FINISHED
Object Rachel True E1055322 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: Rachel True | Statement: [The Craft, castMember, Rachel True]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel True
Context triple: [The Craft, castMember, Rachel True]
  • A. Rachel True chosen
    Rachel True is an American actress best known for her roles in films like "The Craft" and the television series "Half & Half."
  • B. Sarah Trevis
    Sarah Trevis is a British casting director known for her work in film, television, and theatre, and for her former marriage to actor Dougray Scott.
  • C. Rachel Winter
    Rachel Winter is an American film producer best known for her Academy Award–nominated work on the drama "Dallas Buyers Club."
  • D. Kate Tryon
    Kate Tryon is a notable individual distinguished enough to be recognized as a prominent bearer of the Tryon surname.
  • E. Ruby Gentry
    Ruby Gentry is a 1952 American melodrama film directed by King Vidor, starring Jennifer Jones as a poor Southern woman whose passionate love and social struggles lead to tragedy.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03faecd60819091eeaa56c9c8f67d completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d48f17c819088c4d8c2d2b368c8 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:52 a.m.