Triple

T4259575
Position Surface form Disambiguated ID Type / Status
Subject Villeurbanne E96069 entity
Predicate hasNotableDistrict P295 FINISHED
Object Cusset
Cusset is a residential and commercial district in the eastern part of Villeurbanne, near Lyon in eastern France.
 E427445 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: Cusset | Statement: [Villeurbanne, hasNotableDistrict, Cusset]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cusset
Context triple: [Villeurbanne, hasNotableDistrict, Cusset]
  • A. Villedieu
    Villedieu is a commune in southeastern France known for its picturesque setting along the Ouvèze River in the Provence region.
  • B. Cronenbourg
    Cronenbourg is a district of Strasbourg, France, known as a residential and industrial area that is integrated into the city’s public transport network.
  • C. Roussel
    Roussel is a surname of French origin, often used as an alternative spelling of Russell.
  • D. Duras
    Duras is a traditional red wine grape variety from southwest France, known for producing deeply colored, spicy wines with moderate tannins.
  • E. Raoul Meyer
    Raoul Meyer is a Swiss race car driver and businessman best known for his high-profile marriage to actress and model Brigitte Nielsen.
  • 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: Cusset
Triple: [Villeurbanne, hasNotableDistrict, Cusset]
Generated description
Cusset is a residential and commercial district in the eastern part of Villeurbanne, near Lyon in eastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cusset
Target entity description: Cusset is a residential and commercial district in the eastern part of Villeurbanne, near Lyon in eastern France.
  • A. Villedieu
    Villedieu is a commune in southeastern France known for its picturesque setting along the Ouvèze River in the Provence region.
  • B. Cronenbourg
    Cronenbourg is a district of Strasbourg, France, known as a residential and industrial area that is integrated into the city’s public transport network.
  • C. Roussel
    Roussel is a surname of French origin, often used as an alternative spelling of Russell.
  • D. Duras
    Duras is a traditional red wine grape variety from southwest France, known for producing deeply colored, spicy wines with moderate tannins.
  • E. Raoul Meyer
    Raoul Meyer is a Swiss race car driver and businessman best known for his high-profile marriage to actress and model Brigitte Nielsen.
  • 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34f7fe7348190baed8d214268b756 completed March 12, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b78825508190b2b6ca46c8e1b27c completed March 14, 2026, 7:31 p.m.
NEDg Description generation batch_69b5b84b58a081909618d0c108317f92 completed March 14, 2026, 7:34 p.m.
NED2 Entity disambiguation (via description) batch_69b5b8be90c88190a4852c625e326f6b completed March 14, 2026, 7:36 p.m.
Created at: March 12, 2026, 11:06 p.m.