Triple

T16007295
Position Surface form Disambiguated ID Type / Status
Subject Jeffrey Lieber E388250 entity
Predicate notableWork P4 FINISHED
Object Lucifer E1013440 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: Lucifer | Statement: [Jeffrey Lieber, notableWork, Lucifer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucifer
Context triple: [Jeffrey Lieber, notableWork, Lucifer]
  • A. Lucifer
    Lucifer is the fallen angel and ruler of Hell in Dante Alighieri’s Divine Comedy, embodying ultimate evil and the antithesis of divine order.
  • B. Lucifer
    Lucifer is the sly, spoiled pet cat of Lady Tremaine in Disney’s Cinderella, known for tormenting Cinderella and her animal friends.
  • C. Lucifer chosen
    "Lucifer" is an American urban fantasy television series that follows Lucifer Morningstar, the Devil, as he abandons Hell to run a Los Angeles nightclub and consult for the LAPD.
  • D. Lucifer
    Lucifer is a famous 1890 painting by German Symbolist artist Franz von Stuck, depicting a brooding, monumental figure of the fallen angel.
  • E. I, Lucifer
    "I, Lucifer" is a concept album by The Real Tuesday Weld that blends cabaret-pop, jazz, and electronic elements to musically interpret Glen Duncan’s novel of the same name from the Devil’s perspective.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15800246c8190a298c5f96478c396 completed April 16, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf20c5348190b42c2e01e8ef5ea8 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:55 a.m.