Triple

T13087906
Position Surface form Disambiguated ID Type / Status
Subject Ferenc E310384 entity
Predicate equivalentNameInEnglish P3437 FINISHED
Object Francis
Francis is the English equivalent of the given name Ferenc, commonly used in many English-speaking countries.
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: [Ferenc, equivalentNameInEnglish, Francis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francis
Context triple: [Ferenc, equivalentNameInEnglish, Francis]
  • A. Francis
    Francis is the given first name of legendary Los Angeles Lakers play-by-play announcer Chick Hearn.
  • B. Francis
    Francis is the middle name of American seismologist Charles Francis Richter, best known for creating the Richter magnitude scale for measuring earthquakes.
  • C. Francis
    Francis is the given name of Frank Sheeran, the American labor union official and alleged mob hitman whose life inspired the film "The Irishman."
  • D. Francis
    Francis is the given name of American singer and conductor Frank Sinatra Jr., son of legendary entertainer Frank Sinatra.
  • E. Francis
    Francis is a person known primarily through their association as a friend of Heimlich.
  • 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: [Ferenc, equivalentNameInEnglish, Francis]
Generated description
Francis is the English equivalent of the given name Ferenc, commonly used in many English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Francis
Target entity description: Francis is the English equivalent of the given name Ferenc, commonly used in many English-speaking countries.
  • A. Francis
    Francis is a common English surname of Latin origin, historically associated with people from France or those bearing the given name Francis.
  • 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 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 name of Frank Russell, 2nd Earl Russell, a British aristocrat and politician.
  • 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981378dd08190b4f00e4e5df0e480 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d614704481908758cf8691a941ea completed May 3, 2026, 4:59 a.m.
NEDg Description generation batch_69f6db8b74e08190919245104ac7ebd9 completed May 3, 2026, 5:22 a.m.
NED2 Entity disambiguation (via description) batch_69f6dc4db1e0819082f1b7e196e7f0c0 completed May 3, 2026, 5:25 a.m.
Created at: April 9, 2026, 9:02 p.m.