Triple

T19704486
Position Surface form Disambiguated ID Type / Status
Subject Jean Coralli E473176 entity
Predicate givenName P17 FINISHED
Object Jean
Jean is a common French given name used for both males and females, equivalent to "John" or "Jane" in English depending on context.
 E209182 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: Jean | Statement: [Jean Coralli, givenName, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jean
Context triple: [Jean Coralli, givenName, Jean]
  • A. Jean
    Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • B. Jean
    Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
  • C. Jean
    Jean is the central protagonist of the crime drama film "I'm Your Woman," a young mother forced into a perilous life on the run after her husband's criminal activities unravel.
  • D. Jean
    Jean is the given first name of the Canadian novelist Margaret Laurence, a central figure in 20th-century Canadian literature.
  • E. Jean
    Jean is the first name of C. J. Cregg, the fictional White House Press Secretary from the television series "The West Wing."
  • 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: Jean
Triple: [Jean Coralli, givenName, Jean]
Generated description
Jean is a common French given name used for both males and females, equivalent to "John" or "Jane" in English depending on context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jean
Target entity description: Jean is a common French given name used for both males and females, equivalent to "John" or "Jane" in English depending on context.
  • A. Jean chosen
    Jean is a common French given name used for both males and females, equivalent to "John" in English.
  • B. Jean
    Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • C. Jean
    Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
  • D. Jean
    Jean is the given first name of the Canadian novelist Margaret Laurence, a central figure in 20th-century Canadian literature.
  • E. Jean
    Jean is the given first name of American film and television actress Jeff Donnell, known for her roles in mid-20th-century Hollywood productions.
  • 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b998608190a82f23bbf77f7bd2 completed April 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ab98bda48190b61ac274459954bd completed May 15, 2026, 11:26 p.m.
NEDg Description generation batch_6a07acc9e5488190ba55f47af118fca2 completed May 15, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a07ad8aefc4819098768025121123ba completed May 15, 2026, 11:34 p.m.
Created at: April 10, 2026, 1:46 p.m.