Triple

T11690637
Position Surface form Disambiguated ID Type / Status
Subject Francis Arinze E277858 entity
Predicate givenName P17 FINISHED
Object Francis
Francis is a masculine given name of Latin origin, derived from "Franciscus," meaning "Frenchman" or "from France."
E293255 NE FINISHED

How this triple was built (4 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 Arinze, givenName, Francis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francis
Context triple: [Francis Arinze, givenName, Francis]
  • A. Francis
    Francis is the given first name of Daley Thompson, the celebrated British decathlete and double Olympic gold medalist.
  • B. 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."
  • C. Francis
    Francis is the middle name of Samuel Francis Du Pont, a prominent 19th-century U.S. Navy admiral from the Du Pont family.
  • D. Francis
    Francis is the given first name of Scottish former professional footballer Frank McAvennie.
  • E. Francis
    Francis was the given name of Francis of Lorraine, a 16th-century French nobleman who became Duke of Lorraine and played a significant role in European dynastic politics.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Francis
Triple: [Francis Arinze, givenName, Francis]
Generated description
Francis is a masculine given name of Latin origin, derived from "Franciscus," meaning "Frenchman" or "from France."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Francis
Target entity description: Francis is a masculine given name of Latin origin, derived from "Franciscus," meaning "Frenchman" or "from France."
  • A. 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.
  • B. Francis
    Francis is a common English surname of Latin origin, historically associated with people from France or those bearing the given name Francis.
  • C. Francis
    Francis is the given first name of the English actor Frank Finlay, known for his work in film, television, and theatre.
  • D. Francis
    Francis is the given first name of Irish actor and singer Fra Fee, known for his work in film, television, and musical theatre.
  • E. Francis
    Francis is the given first name of Scottish former professional footballer Frank McAvennie.
  • F. None of above.

Provenance (5 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a47a3ddc819098e208611148d15b completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef1451b4708190be9aa0439aface7a completed April 27, 2026, 7:46 a.m.
NEDg Description generation batch_69ef35527f908190b681afdae3aec319 completed April 27, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69ef51ec07ec8190b5cd97cf909388f0 completed April 27, 2026, 12:09 p.m.
Created at: April 8, 2026, 9:40 p.m.