Triple

T16260837
Position Surface form Disambiguated ID Type / Status
Subject Wolf Racing E394749 entity
Predicate owner P347 FINISHED
Object Walter Wolf NE NERFINISHED

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: Walter Wolf | Statement: [Wolf Racing, owner, Walter Wolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Wolf
Context triple: [Wolf Racing, owner, Walter Wolf]
  • A. Walter Wolf chosen
    Walter Wolf is a Slovenian-Canadian businessman best known for his involvement in Formula One through the Wolf Racing team and for his ventures in the oil and tobacco industries.
  • B. Walter Fuchs
    Walter Fuchs is a notable individual who shares the surname Fuchs, recognized enough to be specifically cited among its bearers.
  • C. Walter Willinger
    Walter Willinger is a prominent computer scientist known for his influential work in Internet traffic modeling, network measurement, and the application of fractal and self-similar processes to communication networks.
  • D. Hans Wiegel
    Hans Wiegel is a prominent Dutch liberal politician who served as leader of the VVD and as Deputy Prime Minister of the Netherlands in the late 20th century.
  • E. Walter Wottitz
    Walter Wottitz was a French cinematographer best known for his Academy Award-winning work on the World War II epic film "The Longest Day."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c3e5388190942b0237ab5d1f0f completed April 17, 2026, 2:37 p.m.
Created at: April 10, 2026, 5:04 a.m.