Triple

T23471275
Position Surface form Disambiguated ID Type / Status
Subject Daniel Pratt E570133 entity
Predicate familyName P18 FINISHED
Object Pratt 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: Pratt | Statement: [Daniel Pratt, familyName, Pratt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pratt
Context triple: [Daniel Pratt, familyName, Pratt]
  • A. Pratt chosen
    Pratt is a common English surname borne by various notable individuals across fields such as entertainment, politics, and academia.
  • B. Widener
    Widener is an American surname most prominently associated with a wealthy Philadelphia family known for their influence in business, philanthropy, and the arts.
  • C. Doane
    Doane is a surname most notably associated with William Croswell Doane, the first Episcopal Bishop of Albany and a prominent 19th-century American church leader.
  • D. Princeton
    Princeton is a historic New Jersey town best known as the site of the pivotal 1777 Battle of Princeton during the American Revolutionary War and as home to Princeton University.
  • E. Princeton
    Princeton is a small unincorporated community in Colusa County, California, known for its agricultural surroundings in the Sacramento Valley.
  • 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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a700bd0481908047aa4678217cbd completed April 29, 2026, 6:36 a.m.
Created at: April 17, 2026, 5:55 p.m.