Triple

T2370594
Position Surface form Disambiguated ID Type / Status
Subject Mark Parker E46079 entity
Predicate familyName P18 FINISHED
Object Parker E44427 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: Parker | Statement: [Mark Parker, familyName, Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parker
Context triple: [Mark Parker, familyName, Parker]
  • A. Parker chosen
    Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
  • B. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • C. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • D. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • E. Spencer
    Spencer is the middle name of American author and aviator Anne Spencer Lindbergh, reflecting her family’s naming tradition.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc76f5aec8190867d621e6849258c completed March 7, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8a2b1448190b19179cf379993ee completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:56 p.m.