Triple

T14569140
Position Surface form Disambiguated ID Type / Status
Subject DELAG E341863 entity
Predicate foundedBy P104 FINISHED
Object Banque de la Saône
Banque de la Saône was a French regional bank that played a role in local finance and commerce along the Saône River area.
 E1152262 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: Banque de la Saône | Statement: [DELAG, foundedBy, Banque de la Saône]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Banque de la Saône
Context triple: [DELAG, foundedBy, Banque de la Saône]
  • A. Banque de Dijon
    Banque de Dijon was a regional French bank based in Dijon that played a role in local finance and commerce before being absorbed into larger banking groups.
  • B. Banque de la Loire
    Banque de la Loire is a French regional bank that played a key role in financing local industry and commerce in the Loire area.
  • C. Banque de Besançon
    Banque de Besançon was a regional French bank historically based in the city of Besançon.
  • D. Banque de la Seine
    Banque de la Seine was a French financial institution that played a role in mid-20th-century industrial and commercial development through its involvement in founding companies such as DELAG.
  • E. Banque de l’Est
    Banque de l’Est was a French financial institution active in Eastern France that played a role in regional banking and industrial financing.
  • 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: Banque de la Saône
Triple: [DELAG, foundedBy, Banque de la Saône]
Generated description
Banque de la Saône was a French regional bank that played a role in local finance and commerce along the Saône River area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Banque de la Saône
Target entity description: Banque de la Saône was a French regional bank that played a role in local finance and commerce along the Saône River area.
  • A. Banque de Dijon
    Banque de Dijon was a regional French bank based in Dijon that played a role in local finance and commerce before being absorbed into larger banking groups.
  • B. Banque de la Loire
    Banque de la Loire is a French regional bank that played a key role in financing local industry and commerce in the Loire area.
  • C. Banque de Besançon
    Banque de Besançon was a regional French bank historically based in the city of Besançon.
  • D. Banque de la Seine
    Banque de la Seine was a French financial institution that played a role in mid-20th-century industrial and commercial development through its involvement in founding companies such as DELAG.
  • E. Banque de l’Est
    Banque de l’Est was a French financial institution active in Eastern France that played a role in regional banking and industrial financing.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f2121481908f2385637944785d completed April 14, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01d196d88190a8fa54468b2de1bb completed May 9, 2026, 9:43 a.m.
NEDg Description generation batch_69ff02c10b648190b1e2e04aa0c2596d completed May 9, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69ff066e367c8190a0720fe636355ff8 completed May 9, 2026, 10:03 a.m.
Created at: April 10, 2026, 1:23 a.m.