Triple

T1380655
Position Surface form Disambiguated ID Type / Status
Subject Jean d’Alembert E29329 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.
 E57083 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 d’Alembert, givenName, Jean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jean
Context triple: [Jean d’Alembert, 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 small unincorporated community in Clark County, Nevada, known primarily as a roadside stop and gateway to Las Vegas for travelers from California.
  • C. Alexis
    Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
  • D. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • E. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • 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 d’Alembert, 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 chosen
    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. Alexis
    Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
  • D. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • E. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c319f46481909ba8a69a19b865e5 completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad232309c88190a4ba4f6de7b44035 completed March 8, 2026, 7:20 a.m.
NEDg Description generation batch_69ad253d28b8819093e4aae5c8d36bca completed March 8, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_69ad25cf883c8190ae15dabb02b00a9a completed March 8, 2026, 7:31 a.m.
Created at: March 1, 2026, 7:59 p.m.