Triple

T8201289
Position Surface form Disambiguated ID Type / Status
Subject Logo E191579 entity
Predicate hasImplementation P3697 FINISHED
Object UCBLogo E14675 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: UCBLogo | Statement: [Logo, hasImplementation, UCBLogo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UCBLogo
Context triple: [Logo, hasImplementation, UCBLogo]
  • A. UCB
    UCB is a specialist university in Birmingham, England, known for its vocational and professional courses in areas such as hospitality, tourism, and culinary arts.
  • B. UC Berkeley wordmarks chosen
    UC Berkeley wordmarks are the official typographic logos of the University of California, Berkeley, typically featuring its name in distinctive fonts and colors for branding and identification.
  • C. CUC
    CUC is the national organization representing Unitarian and Unitarian Universalist congregations across Canada, providing support, resources, and coordination for their religious and social justice activities.
  • D. Cal U
    Cal U is a public university located in California, Pennsylvania, known for its career-focused undergraduate and graduate programs.
  • E. UIC
    UIC is the International Union of Railways, a global organization that standardizes and promotes cooperation in the railway sector worldwide.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5df6e7548190846a1afd62ec6d0a completed March 31, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedc49ba4819099762f200c4e6577 completed April 1, 2026, 10:04 a.m.
Created at: March 30, 2026, 5:43 p.m.