Triple

T12974147
Position Surface form Disambiguated ID Type / Status
Subject Compasso d’Oro E321476 entity
Predicate notableRecipient P108 FINISHED
Object Brionvega E987717 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: Brionvega | Statement: [Compasso d’Oro, notableRecipient, Brionvega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brionvega
Context triple: [Compasso d’Oro, notableRecipient, Brionvega]
  • A. Brionvega chosen
    Brionvega is an Italian electronics company renowned for its iconic, design-forward radios and televisions created in collaboration with prominent industrial designers.
  • B. Yvorne
    Yvorne is a small municipality in the canton of Vaud in western Switzerland, known for its vineyards and scenic Alpine surroundings.
  • C. Renaelva
    Renaelva is a river in eastern Norway that flows through Hedmark county before joining the larger Glomma river.
  • D. Wildomar
    Wildomar is a small city in Southern California known for its suburban residential character and location within the rapidly growing Inland Empire region.
  • E. Blaquiere
    Blaquiere was a notable Philhellene known for supporting the Greek struggle for independence in the 19th century.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e4322c08190abd43daadf16097f completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc0b8188190a6a40bb4edf53e25 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 8:37 p.m.