Triple

T3870793
Position Surface form Disambiguated ID Type / Status
Subject Yale Bulldogs men’s track and field E91979 entity
Predicate teamColors P60 FINISHED
Object Yale Blue E1533 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: Yale Blue | Statement: [Yale Bulldogs men’s track and field, teamColors, Yale Blue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yale Blue
Context triple: [Yale Bulldogs men’s track and field, teamColors, Yale Blue]
  • A. Yale Blue chosen
    Yale Blue is a deep, rich shade of blue traditionally associated with academic institutions and collegiate branding.
  • B. Berkeley Blue
    Berkeley Blue is a deep navy shade that serves as one of the primary official colors representing the University of California, Berkeley.
  • C. Columbia blue
    Columbia blue is a light, powdery shade of blue traditionally associated with and popularized by Columbia University.
  • D. Duke blue
    Duke blue is the distinctive deep royal blue shade associated with Duke University’s branding and athletic teams.
  • E. Yonsei blue
    Yonsei blue is the distinctive deep blue color traditionally associated with and prominently used in the identity and branding of Yonsei University.
  • 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_69aed9645f348190a9868e7cef56ab7e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec54b0848190a8d4a0e4df7b6227 completed March 9, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124769c081909111b4bcac6baa78 completed March 14, 2026, 7:46 a.m.
Created at: March 9, 2026, 3:20 p.m.