Triple

T13503023
Position Surface form Disambiguated ID Type / Status
Subject Nico Rosberg E320939 entity
Predicate competedForTeam P60038 FINISHED
Object Mercedes E1042364 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 | Statement: [Nico Rosberg, competedForTeam, Mercedes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mercedes
Context triple: [Nico Rosberg, competedForTeam, Mercedes]
  • A. 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."
  • 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 coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
  • E. Mercedes chosen
    Mercedes is a German Formula One team and automotive manufacturer renowned for its dominant performance in the early hybrid era of F1.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf50f4a48190a44fc537b78c32fd completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d6fde508190865a8e3e391fdf5e completed May 8, 2026, 4:58 a.m.
Created at: April 9, 2026, 9:43 p.m.