Triple

T14397286
Position Surface form Disambiguated ID Type / Status
Subject Jessie E356981 entity
Predicate shortFormOf P43 FINISHED
Object Jean
Jean is a given name, often used in French-speaking regions, that can serve as either a masculine or feminine first name depending on the cultural 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: [Jessie, shortFormOf, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean
Context triple: [Jessie, shortFormOf, 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 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.
  • E. Jean
    Jean is a common French given name used for both males and females, equivalent to "John" in English.
  • 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: [Jessie, shortFormOf, Jean]
Generated description
Jean is a given name, often used in French-speaking regions, that can serve as either a masculine or feminine first name depending on the cultural context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jean
Target entity description: Jean is a given name, often used in French-speaking regions, that can serve as either a masculine or feminine first name depending on the cultural 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 birth name of American actress, comedian, writer, and producer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
  • E. Jean
    Jean is a central character in the Scottish musical film "Sunshine on Leith," which follows the lives and relationships of people in Edinburgh set to the music of The Proclaimers.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90826f908190b3969af9b7cf922f completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bc424f88190ab3a1c1aec61cb40 completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5cf4dedc81908988f13f0fc9f510 completed May 8, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69fd5dcf151c8190959b3240813a1d71 completed May 8, 2026, 3:51 a.m.
Created at: April 10, 2026, 1:17 a.m.