Triple

T16046687
Position Surface form Disambiguated ID Type / Status
Subject Mercedes-AMG CLS 53 E389239 entity
Predicate manufacturer P490 FINISHED
Object Mercedes-AMG E1020713 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: Mercedes-AMG | Statement: [Mercedes-AMG CLS 53, manufacturer, Mercedes-AMG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mercedes-AMG
Context triple: [Mercedes-AMG CLS 53, manufacturer, Mercedes-AMG]
  • A. Mercedes-AMG chosen
    Mercedes-AMG is the high-performance division of Mercedes-Benz, specializing in sport-tuned luxury vehicles and powerful engines.
  • B. Mercedes
    Mercedes is a minor but memorable character in Jack London’s novel "The Call of the Wild," portrayed as a pampered, naive woman whose behavior contributes to the hardship and downfall of her sledding party.
  • C. Mercedes
    Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
  • D. Mercedes
    Mercedes is a coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
  • E. Mercedes
    Mercedes is the given first name of the British former ballerina and television personality Darcey Bussell.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1835eda348190aff492f0ff668cce completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbdbcf248190b7122d61d857e806 completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:56 a.m.