Triple

T18828039
Position Surface form Disambiguated ID Type / Status
Subject Francis Asbury E460443 entity
Predicate givenName P17 FINISHED
Object Francis — 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: Francis | Statement: [Francis Asbury, givenName, Francis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Francis
Context triple: [Francis Asbury, givenName, Francis]
  • A. Francis
    Francis is the given first name of the American actor Frank Morgan, best known for his role as the Wizard in "The Wizard of Oz."
  • B. Francis chosen
    Francis is a masculine given name of Latin origin, commonly used in English-speaking countries and associated with figures such as Saint Francis of Assisi and numerous historical and contemporary personalities.
  • C. Francis
    Francis is the given first name of Scottish former professional footballer Frank McAvennie.
  • D. Francis
    Francis is the given name of Francis John Clarence Westenra Plantagenet Hastings, the 16th Earl of Huntingdon, a British peer and artist.
  • E. Francis
    Francis is the given name of St. Francis de Sales, a 17th-century Catholic bishop renowned for his spiritual writings and gentle approach to religious reform.
  • 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a99554848190933dd2810f5c810f completed April 20, 2026, 4:20 a.m.
Created at: April 10, 2026, 11:56 a.m.