Triple

T14556143
Position Surface form Disambiguated ID Type / Status
Subject Ille E341546 entity
Predicate passesThrough P225 FINISHED
Object Saint-Germain-sur-Ille
Saint-Germain-sur-Ille is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
E1198924 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: Saint-Germain-sur-Ille | Statement: [Ille, passesThrough, Saint-Germain-sur-Ille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Germain-sur-Ille
Context triple: [Ille, passesThrough, Saint-Germain-sur-Ille]
  • A. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • B. Montreuil-sur-Ille
    Montreuil-sur-Ille is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
  • C. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • D. Cholet
    Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
  • E. Saumur
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • 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: Saint-Germain-sur-Ille
Triple: [Ille, passesThrough, Saint-Germain-sur-Ille]
Generated description
Saint-Germain-sur-Ille is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Saint-Germain-sur-Ille
Target entity description: Saint-Germain-sur-Ille is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
  • A. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • B. Montreuil-sur-Ille
    Montreuil-sur-Ille is a small commune in the Ille-et-Vilaine department of Brittany in northwestern France.
  • C. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • D. Cholet
    Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
  • E. Saumur
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f1490881908673f429e5288c86 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fffee0ff948190911c02f6e50ea2bc completed May 10, 2026, 3:43 a.m.
NEDg Description generation batch_6a00007647a08190bff12da75c4a3c02 completed May 10, 2026, 3:50 a.m.
NED2 Entity disambiguation (via description) batch_6a0000e385bc819080e63ced564fe77b completed May 10, 2026, 3:52 a.m.
Created at: April 10, 2026, 1:23 a.m.