Triple

T1564759
Position Surface form Disambiguated ID Type / Status
Subject Jeanne d’Albret E33406 entity
Predicate givenName P17 FINISHED
Object Jeanne
Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
 E191141 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: Jeanne | Statement: [Jeanne d’Albret, givenName, Jeanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jeanne
Context triple: [Jeanne d’Albret, givenName, Jeanne]
  • A. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • 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 first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • D. 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.
  • E. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • 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: Jeanne
Triple: [Jeanne d’Albret, givenName, Jeanne]
Generated description
Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jeanne
Target entity description: Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
  • A. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • 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 first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
  • D. 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.
  • E. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621242188190a7e1deeada7688d8 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad797d8c68819093fb2bcae0a08698 completed March 8, 2026, 1:28 p.m.
NEDg Description generation batch_69ad7a854a68819094cffb51a6b148b9 completed March 8, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69ad7b3fec8881908bd440e22f01b507 completed March 8, 2026, 1:36 p.m.
Created at: March 4, 2026, 7:27 p.m.