Triple

T1640608
Position Surface form Disambiguated ID Type / Status
Subject Bert Bell E35461 entity
Predicate givenName P17 FINISHED
Object De Benneville
De Benneville "Bert" Bell was a prominent American football executive best known as the NFL commissioner who helped modernize and popularize the league in the mid-20th century.
 E186912 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: De Benneville | Statement: [Bert Bell, givenName, De Benneville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: De Benneville
Context triple: [Bert Bell, givenName, De Benneville]
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. La Rivière
    La Rivière is a sector of the town of Gold, recognized as one of its notable local areas.
  • C. La Baie
    La Baie is the French-language brand name used by the Hudson’s Bay Company for its department stores in Quebec and other francophone markets in Canada.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Moulinois
    Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
  • 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: De Benneville
Triple: [Bert Bell, givenName, De Benneville]
Generated description
De Benneville "Bert" Bell was a prominent American football executive best known as the NFL commissioner who helped modernize and popularize the league in the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: De Benneville
Target entity description: De Benneville "Bert" Bell was a prominent American football executive best known as the NFL commissioner who helped modernize and popularize the league in the mid-20th century.
  • A. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • B. La Rivière
    La Rivière is a sector of the town of Gold, recognized as one of its notable local areas.
  • C. La Baie
    La Baie is the French-language brand name used by the Hudson’s Bay Company for its department stores in Quebec and other francophone markets in Canada.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Moulinois
    Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3c883c8190bec1d87ecedf2575 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad609cf8488190ba334bdff2c5e78d completed March 8, 2026, 11:42 a.m.
NEDg Description generation batch_69ad61ff65b881909009c230780a146e completed March 8, 2026, 11:48 a.m.
NED2 Entity disambiguation (via description) batch_69ad62ec3a80819085fef1c378b9abdc completed March 8, 2026, 11:52 a.m.
Created at: March 4, 2026, 7:28 p.m.