Triple

T13944962
Position Surface form Disambiguated ID Type / Status
Subject United States Minister to Prussia E335355 entity
Predicate officeHolderExample P69539 FINISHED
Object Henry Wheaton E78025 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: Henry Wheaton | Statement: [United States Minister to Prussia, officeHolderExample, Henry Wheaton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry Wheaton
Context triple: [United States Minister to Prussia, officeHolderExample, Henry Wheaton]
  • A. Henry Wheaton chosen
    Henry Wheaton was a 19th-century American jurist, diplomat, and pioneering scholar of international law whose writings significantly shaped the field.
  • B. William LeBaron
    William LeBaron was an American film producer and studio executive active during the early 20th century, known for overseeing numerous Hollywood productions in the 1920s and 1930s.
  • C. Henry Bayfield
    Henry Bayfield was a British naval officer and hydrographer known for his extensive 19th-century surveys and mapping of the Great Lakes region of North America.
  • D. Hamilton Wilkes
    Hamilton Wilkes was a 19th-century American yachtsman best known for helping establish the prestigious New York Yacht Club.
  • E. Williams Lea
    Williams Lea is a global business process outsourcing and professional services company specializing in document, information, and customer communication management for corporate clients.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e10f60c81908ee9636e85c070ff completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7d44d848190ab445833e64a6bfc completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:17 p.m.