Triple

T1723314
Position Surface form Disambiguated ID Type / Status
Subject Jean Vanier E37440 entity
Predicate givenName P17 FINISHED
Object Jean
Jean is a common French given name used for both males and females, 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 Vanier, givenName, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean
Context triple: [Jean Vanier, 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 a small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • D. Jeanne
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • E. Alexis
    Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
  • 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 Vanier, givenName, Jean]
Generated description
Jean is a common French given name used for both males and females, 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 used for both males and females, equivalent to "John" in English.
  • 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 small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • 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. Jeanne
    Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • E. Alexis
    Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
  • F. None of above. chosen

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_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa63587ce08190a6a9e6dae11a708c completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf3608208190a27b0f949da83fcd completed March 8, 2026, 8:42 p.m.
NEDg Description generation batch_69addfe46b388190b319043170253701 completed March 8, 2026, 8:45 p.m.
NED2 Entity disambiguation (via description) batch_69ade08d0ce0819097beb901dbb39d89 completed March 8, 2026, 8:48 p.m.
Created at: March 4, 2026, 7:30 p.m.