Triple

T22677674
Position Surface form Disambiguated ID Type / Status
Subject John E560388 entity
Predicate hasVariant P455 FINISHED
Object Jean
Jean is a given name used in various languages, commonly as the French form of "John" and as both a masculine and feminine name in different cultures.
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: [John, hasVariant, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean
Context triple: [John, hasVariant, 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: [John, hasVariant, Jean]
Generated description
Jean is a given name used in various languages, commonly as the French form of "John" and as both a masculine and feminine name in different cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jean
Target entity description: Jean is a given name used in various languages, commonly as the French form of "John" and as both a masculine and feminine name in different cultures.
  • 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 name of the actress better known professionally as Vivean Gray, recognized for her roles in British and Australian film and television.
  • C. Jean
    Jean is a person connected in some way to Johannes, likely as a relative, associate, or close acquaintance.
  • D. Jean
    Jean is a surname most notably associated with Spanish DJ, producer, and composer Carlos Jean.
  • 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_69e2454bfd00819099115715a22cb057 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1785d93e48190b37d11642b0cb123 completed April 29, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b73f115cc819085e82dfa9f32ffa8 completed May 18, 2026, 8:17 p.m.
NEDg Description generation batch_6a0b752363a48190af3733c8ca995c25 completed May 18, 2026, 8:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0b7601fda88190bbfa04e7eb240f65 completed May 18, 2026, 8:26 p.m.
Created at: April 17, 2026, 3:11 p.m.