Triple

T2123799
Position Surface form Disambiguated ID Type / Status
Subject Châteauroux E43984 entity
Predicate hasMayor P185 FINISHED
Object Gil Avérous
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
E239990 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: Gil Avérous | Statement: [Châteauroux, hasMayor, Gil Avérous]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gil Avérous
Context triple: [Châteauroux, hasMayor, Gil Avérous]
  • A. 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.
  • B. Paul Seydor
    Paul Seydor is a film editor and scholar best known for his work on Sam Peckinpah’s films and his writings on American cinema.
  • C. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • D. Julien Flegenheimer
    Julien Flegenheimer was an architect best known for his role in designing the Palais des Nations, the former League of Nations headquarters in Geneva.
  • E. Jean-Claude Olivier
    Jean-Claude Olivier is a writer associated with the Juicy brand or publication.
  • 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: Gil Avérous
Triple: [Châteauroux, hasMayor, Gil Avérous]
Generated description
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gil Avérous
Target entity description: Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • A. 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.
  • B. Paul Seydor
    Paul Seydor is a film editor and scholar best known for his work on Sam Peckinpah’s films and his writings on American cinema.
  • C. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • D. Julien Flegenheimer
    Julien Flegenheimer was an architect best known for his role in designing the Palais des Nations, the former League of Nations headquarters in Geneva.
  • E. Jean-Claude Olivier
    Jean-Claude Olivier is a writer associated with the Juicy brand or publication.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb55cb2c8190aab8199da3335032 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58cf2a588190a59dc1ae5d684538 completed March 9, 2026, 5:21 a.m.
NEDg Description generation batch_69ae599c6b288190b7e173ffc505c605 completed March 9, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae5a42675c8190a019034e8a6bda21 completed March 9, 2026, 5:27 a.m.
Created at: March 4, 2026, 7:44 p.m.