Triple

T19001462
Position Surface form Disambiguated ID Type / Status
Subject Francis X. Suarez E464963 entity
Predicate givenName P17 FINISHED
Object Francis
Francis is a common masculine given name of Latin origin, widely used in English-speaking and other Christian-influenced cultures.
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 X. Suarez, givenName, Francis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francis
Context triple: [Francis X. Suarez, givenName, Francis]
  • A. Francis
    Francis is the given first name of legendary Los Angeles Lakers play-by-play announcer Chick Hearn.
  • B. Francis
    Francis was a German nobleman who served as Duke of Saxe-Coburg-Saalfeld in the late 18th and early 19th centuries.
  • C. Francis
    Francis is the middle name of American motion picture and television pioneer Charles Francis Jenkins.
  • D. Francis
    Francis is the given name of Sir Francis Walsingham, the principal secretary and spymaster to Queen Elizabeth I of England.
  • E. Francis
    Francis is the formal given name of Frank McCourt, the Irish-American teacher and Pulitzer Prize–winning author of the memoir "Angela's Ashes."
  • 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 X. Suarez, givenName, Francis]
Generated description
Francis is a common masculine given name of Latin origin, widely used in English-speaking and other Christian-influenced cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Francis
Target entity description: Francis is a common masculine given name of Latin origin, widely used in English-speaking and other Christian-influenced cultures.
  • 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 name of St. Francis de Sales, a 17th-century Catholic bishop renowned for his spiritual writings and gentle approach to religious reform.
  • D. Francis
    Francis is the papal name of the current head of the Roman Catholic Church, known for his emphasis on humility, social justice, and interfaith dialogue.
  • E. Francis
    Francis is the given first name of Irish actor and singer Fra Fee, known for his work in film, television, and musical theatre.
  • 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d687cb2081909bf3ac761e292f22 completed April 20, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05b45b9ca0819090a85f5708e9c632 completed May 14, 2026, 11:39 a.m.
NEDg Description generation batch_6a05b68205948190a6846e2cd8ba66ae completed May 14, 2026, 11:48 a.m.
NED2 Entity disambiguation (via description) batch_6a05b73aa91c8190abe816e72d2f56f7 completed May 14, 2026, 11:51 a.m.
Created at: April 10, 2026, 12:01 p.m.