Triple

T12959445
Position Surface form Disambiguated ID Type / Status
Subject Tramway de Tours E310099 entity
Predicate servesCommune P42362 FINISHED
Object La Riche
La Riche is a commune in central France, located near the city of Tours in the Indre-et-Loire department.
 E1012824 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: La Riche | Statement: [Tramway de Tours, servesCommune, La Riche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Riche
Context triple: [Tramway de Tours, servesCommune, La Riche]
  • A. Fortune carrée
    Fortune carrée is an adventure novel by French writer Joseph Kessel, set largely at sea and in the Middle East, exploring themes of freedom, danger, and human resilience.
  • B. Trésor
    Trésor is a classic and bestselling women’s fragrance by Lancôme, renowned for its romantic, elegant, and timeless scent.
  • C. Le Muy
    Le Muy is a commune in southeastern France’s Var department, known for its Provençal character and location near the Mediterranean coast.
  • D. Bonne Pioche
    Bonne Pioche is a French film and television production company known internationally for producing acclaimed documentaries such as "March of the Penguins."
  • E. Le Prince
    Le Prince is a French surname most notably associated with Jean-Baptiste Le Prince, an 18th-century painter and etcher known for his scenes inspired by travels in Russia.
  • 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: La Riche
Triple: [Tramway de Tours, servesCommune, La Riche]
Generated description
La Riche is a commune in central France, located near the city of Tours in the Indre-et-Loire department.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: La Riche
Target entity description: La Riche is a commune in central France, located near the city of Tours in the Indre-et-Loire department.
  • A. Fortune carrée
    Fortune carrée is an adventure novel by French writer Joseph Kessel, set largely at sea and in the Middle East, exploring themes of freedom, danger, and human resilience.
  • B. Trésor
    Trésor is a classic and bestselling women’s fragrance by Lancôme, renowned for its romantic, elegant, and timeless scent.
  • C. Le Muy
    Le Muy is a commune in southeastern France’s Var department, known for its Provençal character and location near the Mediterranean coast.
  • D. Bonne Pioche
    Bonne Pioche is a French film and television production company known internationally for producing acclaimed documentaries such as "March of the Penguins."
  • E. Le Prince
    Le Prince is a French surname most notably associated with Jean-Baptiste Le Prince, an 18th-century painter and etcher known for his scenes inspired by travels in Russia.
  • 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e2e44908190bb8b43fc5c3b8a8a completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8e006cc819091e5f4b044cadea4 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9dac2c88190850304023f156969 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb2602848190b9588134c71d0ef4 completed May 3, 2026, 3:04 a.m.
Created at: April 9, 2026, 5:44 p.m.