Triple

T14080464
Position Surface form Disambiguated ID Type / Status
Subject Stigmata E338851 entity
Predicate title P38 FINISHED
Object Stigmata E338851 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: Stigmata | Statement: [Stigmata, title, Stigmata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stigmata
Context triple: [Stigmata, title, Stigmata]
  • A. Stigmata chosen
    Stigmata is a 1999 supernatural horror film in which a young woman inexplicably manifests the wounds of Christ, drawing the attention of the Catholic Church.
  • B. The Passion
    The Passion is a novel by Jeanette Winterson that blends historical fiction and magical realism to explore love, war, and obsession during the Napoleonic era.
  • C. Passio
    Passio is a minimalist sacred choral work by Estonian composer Arvo Pärt that sets the Latin text of the Passion according to St. John.
  • D. Petals of Blood
    Petals of Blood is a politically charged novel by Kenyan writer Ngũgĩ wa Thiong’o that critiques postcolonial corruption and neocolonial exploitation in Kenya.
  • E. Lady of the Angels
    Lady of the Angels is a Marian title that honors the Virgin Mary as the queen and protector of the angelic hosts.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5f759c81909bfd60ab35b0937b completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb672c08081908e1ff9030745776a completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:21 p.m.