Triple

T10797483
Position Surface form Disambiguated ID Type / Status
Subject Gradignan E254747 entity
Predicate hasMayor P185 FINISHED
Object Michel Labardin
Michel Labardin is a French local politician who serves as the mayor of the commune of Gradignan in southwestern France.
E1097450 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: Michel Labardin | Statement: [Gradignan, hasMayor, Michel Labardin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michel Labardin
Context triple: [Gradignan, hasMayor, Michel Labardin]
  • A. Pierre Lacotte
    Pierre Lacotte was a renowned French choreographer and ballet master celebrated for reviving and reconstructing 19th-century Romantic ballets.
  • B. Pierre Authier
    Pierre Authier is a French automotive designer best known for his work on contemporary Peugeot models, including the popular 208.
  • C. Claude Mabillard
    Claude Mabillard is a Swiss engineer and roller coaster designer best known as the co-founder of the renowned roller coaster manufacturing company Bolliger & Mabillard.
  • D. Georges Récipon
    Georges Récipon was a French sculptor best known for his ornate allegorical sculptures and monumental works in Paris during the late 19th and early 20th centuries.
  • E. Henri Lebasque
    Henri Lebasque was a French post-impressionist painter known for his luminous use of color and intimate domestic and landscape scenes.
  • 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: Michel Labardin
Triple: [Gradignan, hasMayor, Michel Labardin]
Generated description
Michel Labardin is a French local politician who serves as the mayor of the commune of Gradignan in southwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michel Labardin
Target entity description: Michel Labardin is a French local politician who serves as the mayor of the commune of Gradignan in southwestern France.
  • A. Pierre Lacotte
    Pierre Lacotte was a renowned French choreographer and ballet master celebrated for reviving and reconstructing 19th-century Romantic ballets.
  • B. Pierre Authier
    Pierre Authier is a French automotive designer best known for his work on contemporary Peugeot models, including the popular 208.
  • C. Claude Mabillard
    Claude Mabillard is a Swiss engineer and roller coaster designer best known as the co-founder of the renowned roller coaster manufacturing company Bolliger & Mabillard.
  • D. Georges Récipon
    Georges Récipon was a French sculptor best known for his ornate allegorical sculptures and monumental works in Paris during the late 19th and early 20th centuries.
  • E. Henri Lebasque
    Henri Lebasque was a French post-impressionist painter known for his luminous use of color and intimate domestic and landscape scenes.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73333dc4081909faa40c10bce2735 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd54f264d48190be636796d694ceb1 completed May 8, 2026, 3:13 a.m.
NEDg Description generation batch_69fd570e482881909532000eebd169d1 completed May 8, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69fd57710f648190a1344ac1363acce1 completed May 8, 2026, 3:24 a.m.
Created at: April 8, 2026, 9:17 p.m.