Triple

T13814118
Position Surface form Disambiguated ID Type / Status
Subject Stephen Surjik E331969 entity
Predicate directed P7373 FINISHED
Object Lucifer (TV series) E780290 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 (TV series) | Statement: [Stephen Surjik, directed, Lucifer (TV series)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucifer (TV series)
Context triple: [Stephen Surjik, directed, Lucifer (TV series)]
  • A. Lucifer (TV series) chosen
    Lucifer is an American fantasy crime drama television series that follows the Devil as he abandons Hell to run a nightclub in Los Angeles and consult for the LAPD.
  • B. 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.
  • C. Lucifer
    Lucifer is the sly, spoiled pet cat of Lady Tremaine in Disney’s Cinderella, known for tormenting Cinderella and her animal friends.
  • D. Lucifer
    "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.
  • E. Lucifer Falls
    Lucifer Falls is a dramatic multi-tiered waterfall in New York’s Finger Lakes region, known for its steep gorge setting and scenic hiking trails.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de027198f8819095da3e714ac241f5 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0e6d5cc819087ccdbfc00f16542 completed May 3, 2026, 9:40 p.m.
Created at: April 9, 2026, 10:12 p.m.