Triple

T5278301
Position Surface form Disambiguated ID Type / Status
Subject Kongfrontation E119427 entity
Predicate manufacturer P490 FINISHED
Object Universal Creative E114328 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: Universal Creative | Statement: [Kongfrontation, manufacturer, Universal Creative]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universal Creative
Context triple: [Kongfrontation, manufacturer, Universal Creative]
  • A. Universal Creative chosen
    Universal Creative is the design and development division of Universal Parks & Resorts responsible for creating many of its iconic theme park attractions and experiences.
  • B. CREA
    CREA is a large reference corpus of contemporary Spanish used for linguistic research and language analysis.
  • C. CREI
    CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
  • D. Créative Technologie
    Créative Technologie is Citroën’s modern brand slogan, emphasizing the company’s focus on innovative, design-led automotive engineering and technology.
  • E. The Creative School
    The Creative School is a renowned hub for media, design, and creative industries education within Toronto Metropolitan University, offering innovative programs that blend theory, practice, and industry collaboration.
  • 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_69bd446d05a8819092ad333a3f9c8d5c completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84c2eab881908698a14b116a3bfa completed March 20, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10d839dc8190a9f63740c6bd31a0 completed March 21, 2026, 9:42 p.m.
Created at: March 20, 2026, 1:51 p.m.