Triple

T15104860
Position Surface form Disambiguated ID Type / Status
Subject Sienna Brooks E360762 entity
Predicate appearsIn P795 FINISHED
Object Inferno (novel) E365248 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: Inferno (novel) | Statement: [Sienna Brooks, appearsIn, Inferno (novel)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inferno (novel)
Context triple: [Sienna Brooks, appearsIn, 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 (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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00588f35481909674f161bf0f3918 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae28e99881908156909e553c2538 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:05 a.m.