Triple

T2859846
Position Surface form Disambiguated ID Type / Status
Subject Marie Souvestre E63292 entity
Predicate familyName P18 FINISHED
Object Souvestre
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
 E306487 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: Souvestre | Statement: [Marie Souvestre, familyName, Souvestre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Souvestre
Context triple: [Marie Souvestre, familyName, Souvestre]
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • C. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • D. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • E. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • 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: Souvestre
Triple: [Marie Souvestre, familyName, Souvestre]
Generated description
Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Souvestre
Target entity description: Souvestre is a French surname notably borne by educator Marie Souvestre, known for her progressive influence on women’s education in the 19th century.
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • C. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • D. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • E. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • 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_69ab4c41e8c08190a9e8f5249cc12610 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf8aec3c8190a4168d8c916b5268 completed March 7, 2026, 8:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d972aa481908f6cb5f27706990c completed March 10, 2026, 1:33 p.m.
NEDg Description generation batch_69b021fbc2808190b415fd8af934cf73 completed March 10, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_69b02656f8488190ab0d715d1634b6a7 completed March 10, 2026, 2:10 p.m.
Created at: March 6, 2026, 10:02 p.m.