Triple

T21061590
Position Surface form Disambiguated ID Type / Status
Subject Daniel Petrie E518860 entity
Predicate notableWork P4 FINISHED
Object Sybil NE NERFINISHED

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: Sybil | Statement: [Daniel Petrie, notableWork, Sybil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sybil
Context triple: [Daniel Petrie, notableWork, Sybil]
  • A. Sybil
    Sybil is a character from the fantasy film "The Magic Sword," known for her role in the story’s magical and adventurous narrative.
  • B. Sybil
    Sybil was an illegitimate daughter of King Henry I of England, known primarily through her royal lineage and connections within the Anglo-Norman nobility.
  • C. Sybil
    Sybil is an American R&B and pop singer best known for her late-1980s and early-1990s hits, including popular covers of classic soul songs.
  • D. Sybil chosen
    Sybil is a 1976 television film about a woman with dissociative identity disorder, best known for Sally Field’s acclaimed, Emmy-winning performance in the title role.
  • E. Sybil
    Sybil is a feminine given name of Greek origin, historically associated with prophetesses and later borne by various notable women in arts and literature.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b505ef108190b25dd4033e2ff7eb completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6feb064a48190b892b78e27e8d0fa completed April 21, 2026, 4:36 a.m.
Created at: April 16, 2026, 2:38 p.m.