Triple

T21944264
Position Surface form Disambiguated ID Type / Status
Subject Inferno (2016 film) E541895 entity
Predicate basedOn P98 FINISHED
Object Inferno (novel) 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: Inferno (novel) | Statement: [Inferno (2016 film), basedOn, Inferno (novel)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inferno (novel)
Context triple: [Inferno (2016 film), basedOn, Inferno (novel)]
  • A. Inferno (novel) chosen
    "Inferno" is a 2013 mystery-thriller novel by Dan Brown featuring symbologist Robert Langdon as he races across Europe to unravel a conspiracy linked to Dante Alighieri’s "Divine Comedy" and a deadly global threat.
  • B. Inferno
    Inferno is the first cantica of Dante Alighieri’s Divine Comedy, depicting the poet’s allegorical journey through the nine circles of Hell.
  • C. Inferno
    "Inferno" is a 1953 Technicolor 3D film noir thriller starring William Lundigan alongside Robert Ryan and Rhonda Fleming, noted for its desert survival plot and innovative use of 3D cinematography.
  • D. Inferno
    Inferno is a distributed operating system developed at Bell Labs, known for its use of the Limbo programming language and its focus on portable, networked computing.
  • E. Inferno
    Inferno is one of the most iconic and strategically complex bomb defusal maps in Counter-Strike, known for its tight chokepoints and intense mid and banana control battles.
  • 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1242688988190a7b8f033c49368de completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:56 p.m.