Triple

T18205075
Position Surface form Disambiguated ID Type / Status
Subject DeiT E435881 entity
Predicate hasAuthor P4244 FINISHED
Object Matthieu Cord
Matthieu Cord is a French computer vision and machine learning researcher known for his work on deep learning methods, including contributions to the DeiT vision transformer model.
 E1313855 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: Matthieu Cord | Statement: [DeiT, hasAuthor, Matthieu Cord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Matthieu Cord
Context triple: [DeiT, hasAuthor, Matthieu Cord]
  • A. Mathieu Drach
    Mathieu Drach is the son of French actress Marie-José Nat and is primarily known in relation to his mother's career in French cinema.
  • B. Mathieu Klein
    Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
  • C. Mathieu Froment
    Mathieu Froment is the central character of Émile Zola’s novel "Fécondité," embodying the author’s exploration of family, morality, and social responsibility in turn-of-the-century France.
  • D. Matthieu Rougé
    Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
  • E. Mathias Moncorgé
    Mathias Moncorgé is a French actor and horse racing professional, best known as the son of legendary film star Jean Gabin.
  • 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: Matthieu Cord
Triple: [DeiT, hasAuthor, Matthieu Cord]
Generated description
Matthieu Cord is a French computer vision and machine learning researcher known for his work on deep learning methods, including contributions to the DeiT vision transformer model.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Matthieu Cord
Target entity description: Matthieu Cord is a French computer vision and machine learning researcher known for his work on deep learning methods, including contributions to the DeiT vision transformer model.
  • A. Mathieu Drach
    Mathieu Drach is the son of French actress Marie-José Nat and is primarily known in relation to his mother's career in French cinema.
  • B. Mathieu Klein
    Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
  • C. Mathieu Froment
    Mathieu Froment is the central character of Émile Zola’s novel "Fécondité," embodying the author’s exploration of family, morality, and social responsibility in turn-of-the-century France.
  • D. Matthieu Rougé
    Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
  • E. Mathias Moncorgé
    Mathias Moncorgé is a French actor and horse racing professional, best known as the son of legendary film star Jean Gabin.
  • 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03ac61328c8190ac6c795e74d35705 completed May 12, 2026, 10:40 p.m.
NEDg Description generation batch_6a03ad67e85c81909759b40b9dfd2d12 completed May 12, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_6a03aede6ea481908bb9acdb2ff17e9a completed May 12, 2026, 10:51 p.m.
Created at: April 10, 2026, 10:32 a.m.