Triple

T10011215
Position Surface form Disambiguated ID Type / Status
Subject Bojan Bazelli E199376 entity
Predicate workedOn P3 FINISHED
Object Spectral E38405 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: Spectral | Statement: [Bojan Bazelli, workedOn, Spectral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spectral
Context triple: [Bojan Bazelli, workedOn, Spectral]
  • A. Spectral chosen
    Spectral is a 2016 military science fiction film that follows a special-ops team confronting ghostly entities in a war-torn Eastern European city.
  • B. SPECTRA
    SPECTRA is an advanced integrated electronic warfare and self-protection suite used on modern combat aircraft, notably the Dassault Rafale, to detect, jam, and counter threats.
  • C. Spectrum
    Spectrum is a major American telecommunications brand providing cable television, internet, and phone services, owned by Charter Communications.
  • D. Spectrum
    Spectrum is a collection of essays by historian and political theorist Perry Anderson that surveys and critiques major currents in modern political and intellectual thought.
  • E. Spectrum
    Spectrum was a historic indoor sports and entertainment arena in Philadelphia that hosted professional hockey, basketball, concerts, and major events from the late 1960s until its closure and demolition.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd3b68888190b8a325b52d57c5b8 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e5476f408190b8921cd4343c3af9 completed April 5, 2026, 10:42 p.m.
Created at: March 30, 2026, 8:52 p.m.