Triple

T4281617
Position Surface form Disambiguated ID Type / Status
Subject Ernst B. Haas E97162 entity
Predicate familyName P18 FINISHED
Object Haas E239533 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: Haas | Statement: [Ernst B. Haas, familyName, Haas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haas
Context triple: [Ernst B. Haas, familyName, Haas]
  • A. Haas chosen
    Haas is a German-origin surname borne by numerous individuals worldwide, including several notable figures in fields such as sports, science, and the arts.
  • B. Haas F1 Team
    Haas F1 Team is an American-owned Formula One racing team that competes in the FIA Formula One World Championship.
  • C. Dallara
    Dallara is an Italian race car manufacturer renowned for designing and building chassis for top-level motorsport series worldwide, including IndyCar.
  • 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 a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and fishing-based local economy.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3503938f481909505e0a322dd2b6c completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7bb0168819082a49347fdfe0997 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.