Triple

T1124542
Position Surface form Disambiguated ID Type / Status
Subject Louis Dieudonné E24688 entity
Predicate employer P7 FINISHED
Object Louvois
Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
 E138334 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: Louvois | Statement: [Louis Dieudonné, employer, Louvois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Louvois
Context triple: [Louis Dieudonné, employer, Louvois]
  • A. Jougne
    Jougne is a small French commune in the Doubs department of the Bourgogne-Franche-Comté region, known for its location near the Swiss border in the Jura Mountains.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • D. Issoire
    Issoire is a historic town in central France’s Auvergne region, known for its Romanesque architecture and location in the valley of the Allier River.
  • E. Corine
    Corine is a feminine given name used in various European countries, often considered a variant of "Corinne."
  • 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: Louvois
Triple: [Louis Dieudonné, employer, Louvois]
Generated description
Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Louvois
Target entity description: Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
  • A. Jougne
    Jougne is a small French commune in the Doubs department of the Bourgogne-Franche-Comté region, known for its location near the Swiss border in the Jura Mountains.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Casteau
    Casteau is a village in Belgium best known as the site of NATO’s Supreme Headquarters Allied Powers Europe (SHAPE).
  • D. Issoire
    Issoire is a historic town in central France’s Auvergne region, known for its Romanesque architecture and location in the valley of the Allier River.
  • E. Corine
    Corine is a feminine given name used in various European countries, often considered a variant of "Corinne."
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbd92a8c8190a16e55f3f739010f completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f2dc92481909ee6d9d6d4257f1b completed March 7, 2026, 7:40 p.m.
NEDg Description generation batch_69ac7f9a55dc819098204d53aac70ef3 completed March 7, 2026, 7:42 p.m.
NED2 Entity disambiguation (via description) batch_69ac80c3c6b08190a99119f5661c0157 completed March 7, 2026, 7:47 p.m.
Created at: March 1, 2026, 7:44 p.m.