Triple

T9561808
Position Surface form Disambiguated ID Type / Status
Subject Lisieux E230690 entity
Predicate demonym P191 FINISHED
Object Lexovienne
Lexovienne is the French term for a female inhabitant or native of the town of Lisieux in Normandy.
 E806559 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: Lexovienne | Statement: [Lisieux, demonym, Lexovienne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lexovienne
Context triple: [Lisieux, demonym, Lexovienne]
  • A. Laviolette
    Laviolette was a 17th-century French military officer and colonial administrator best known for establishing the settlement that became the city of Trois-Rivières in New France.
  • B. Crevant-Laveine
    Crevant-Laveine is a small commune in central France’s Puy-de-Dôme department, characterized by its rural setting and traditional Auvergne landscape.
  • C. Lierneux
    Lierneux is a rural municipality in the province of Liège in Wallonia, Belgium, known for its forests, valleys, and quiet countryside.
  • D. Levasy
    Levasy is a small city located in Jackson County in the U.S. state of Missouri.
  • E. Feuillant
    The Feuillants were a moderate monarchist political faction during the French Revolution that supported a constitutional monarchy and opposed the more radical Jacobins.
  • 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: Lexovienne
Triple: [Lisieux, demonym, Lexovienne]
Generated description
Lexovienne is the French term for a female inhabitant or native of the town of Lisieux in Normandy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lexovienne
Target entity description: Lexovienne is the French term for a female inhabitant or native of the town of Lisieux in Normandy.
  • A. Laviolette
    Laviolette was a 17th-century French military officer and colonial administrator best known for establishing the settlement that became the city of Trois-Rivières in New France.
  • B. Crevant-Laveine
    Crevant-Laveine is a small commune in central France’s Puy-de-Dôme department, characterized by its rural setting and traditional Auvergne landscape.
  • C. Lierneux
    Lierneux is a rural municipality in the province of Liège in Wallonia, Belgium, known for its forests, valleys, and quiet countryside.
  • D. Levasy
    Levasy is a small city located in Jackson County in the U.S. state of Missouri.
  • E. Feuillant
    The Feuillants were a moderate monarchist political faction during the French Revolution that supported a constitutional monarchy and opposed the more radical Jacobins.
  • 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_69ca847e53a88190a60eed7e02257f10 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd994d31e08190b139f5ad10d8ea31 completed April 1, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69d152a014a48190925d52967e1fbffe completed April 4, 2026, 6:04 p.m.
NEDg Description generation batch_69d1539bad8481909f9bd060aa3b651c completed April 4, 2026, 6:08 p.m.
NED2 Entity disambiguation (via description) batch_69d154567f408190a848eea4ca905fb6 completed April 4, 2026, 6:11 p.m.
Created at: March 30, 2026, 8:03 p.m.