Triple

T76825
Position Surface form Disambiguated ID Type / Status
Subject Oski the Bear E1534 entity
Predicate shortName P43 FINISHED
Object Oski E1534 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: Oski | Statement: [Oski the Bear, shortName, Oski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oski
Context triple: [Oski the Bear, shortName, Oski]
  • A. Oski the Bear chosen
    Oski the Bear is the costumed, cartoon-style bear character who serves as the spirited athletic and school pride symbol for the University of California, Berkeley.
  • B. Marquette
    Marquette is a city in Michigan’s Upper Peninsula known as a key shipping and commercial hub on the southern shore of Lake Superior.
  • C. Pitt
    Pitt is the surname of William Pitt the Elder, an influential 18th-century British statesman and prime minister known for his leadership during the Seven Years' War.
  • D. University of Illinois at Urbana–Champaign
    The University of Illinois at Urbana–Champaign is a major American public research university known for its strong engineering, computer science, and information science programs.
  • E. Oregon State University
    Oregon State University is a public research university in Corvallis, Oregon, known for its strong programs in engineering, forestry, and agricultural sciences.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f1d20b88190b66836cc018e52e1 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26241d4c08190885dab6aef75dcf3 completed Feb. 28, 2026, 3:34 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.