Triple

T14991744
Position Surface form Disambiguated ID Type / Status
Subject Brenner E373850 entity
Predicate hasNotableBearer P458 FINISHED
Object Joël Brenner
Joël Brenner is an American lawyer and former U.S. national counterintelligence executive known for his work on intelligence, cybersecurity, and privacy issues.
E1132344 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: Joël Brenner | Statement: [Brenner, hasNotableBearer, Joël Brenner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joël Brenner
Context triple: [Brenner, hasNotableBearer, Joël Brenner]
  • A. Marc Breitman
    Marc Breitman is a French architect known for his postmodern and classical-inspired urban projects, including major public buildings in Paris.
  • B. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • C. Éric Weill
    Éric Weill was a French philosopher known for his work on rationality, history, and political thought in the 20th century.
  • D. Luc Jobin
    Luc Jobin is a Canadian business executive best known for serving as president and CEO of Canadian National Railway and holding senior leadership roles in major international corporations.
  • E. Serge D’Elia
    Serge D’Elia is an entrepreneur best known as a founder of the iconic skate and streetwear shoe brand Vans.
  • 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: Joël Brenner
Triple: [Brenner, hasNotableBearer, Joël Brenner]
Generated description
Joël Brenner is an American lawyer and former U.S. national counterintelligence executive known for his work on intelligence, cybersecurity, and privacy issues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Joël Brenner
Target entity description: Joël Brenner is an American lawyer and former U.S. national counterintelligence executive known for his work on intelligence, cybersecurity, and privacy issues.
  • A. Marc Breitman
    Marc Breitman is a French architect known for his postmodern and classical-inspired urban projects, including major public buildings in Paris.
  • B. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • C. Éric Weill
    Éric Weill was a French philosopher known for his work on rationality, history, and political thought in the 20th century.
  • D. Luc Jobin
    Luc Jobin is a Canadian business executive best known for serving as president and CEO of Canadian National Railway and holding senior leadership roles in major international corporations.
  • E. Serge D’Elia
    Serge D’Elia is an entrepreneur best known as a founder of the iconic skate and streetwear shoe brand Vans.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded715db408190b44e8a8452c79764 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969842848190a030db797c851fed completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe983820f88190843361b0ac391d38 completed May 9, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69fe98b18ab48190b2a47418904e6643 completed May 9, 2026, 2:15 a.m.
Created at: April 10, 2026, 2:53 a.m.