Triple

T20153597
Position Surface form Disambiguated ID Type / Status
Subject Jean Cavaillès E491497 entity
Predicate givenName P17 FINISHED
Object Jean
Jean is a common French given name traditionally used for males, equivalent to "John" in English.
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 Cavaillès, givenName, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean
Context triple: [Jean Cavaillès, 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 fictional mother character from the film "Sweet Sixteen."
  • 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 name of the actress better known professionally as Vivean Gray, recognized for her roles in British and Australian film and television.
  • E. Jean
    Jean is a fictional character associated with the story of the rhinoceros, likely from Eugène Ionesco’s absurdist play "Rhinocéros."
  • 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 Cavaillès, givenName, Jean]
Generated description
Jean is a common French given name traditionally used for males, equivalent to "John" in English.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jean
Target entity description: Jean is a common French given name traditionally used for males, equivalent to "John" in English.
  • 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 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 given name of the actress better known professionally as Vivean Gray, recognized for her roles in British and Australian film and television.
  • D. 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.
  • E. Jean
    Jean is the given first name of the Canadian novelist Margaret Laurence, a central figure in 20th-century Canadian literature.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667de9bec8190836887c86dbcf28d completed April 20, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0834743ea88190a30384ab16826485 completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a0835cfd5548190bd29237b0cc08b9e completed May 16, 2026, 9:16 a.m.
NED2 Entity disambiguation (via description) batch_6a083666e9188190b5c62e2f0e7b123e completed May 16, 2026, 9:18 a.m.
Created at: April 11, 2026, 11:34 p.m.