Triple

T14011892
Position Surface form Disambiguated ID Type / Status
Subject Mercedes-AMG S 63 E337101 entity
Predicate brand P1500 FINISHED
Object Mercedes-Benz E11202 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-Benz | Statement: [Mercedes-AMG S 63, brand, Mercedes-Benz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mercedes-Benz
Context triple: [Mercedes-AMG S 63, brand, Mercedes-Benz]
  • A. Mercedes-Benz chosen
    Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
  • B. Mercedes
    Mercedes is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and fishing-based local economy.
  • C. 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.
  • D. 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."
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb6419a3c8190bfaeab65f3909474 completed May 7, 2026, 3:56 p.m.
Created at: April 9, 2026, 10:19 p.m.