Triple
T12397683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AJ Auxerre |
E296159
|
entity |
| Predicate | manager |
P2962
|
FINISHED |
| Object |
Christophe Pélissier
Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
|
E995004
|
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: Christophe Pélissier | Statement: [AJ Auxerre, manager, Christophe Pélissier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christophe Pélissier Context triple: [AJ Auxerre, manager, Christophe Pélissier]
-
A.
Christophe Le Friant
Christophe Le Friant is a French DJ, record producer, and remixer best known under his stage name Bob Sinclar, a prominent figure in the international house music scene.
-
B.
Laurent Chalumeau
Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
-
C.
Laurent Mauvignier
Laurent Mauvignier is a contemporary French novelist known for his psychologically intense, formally innovative works that often explore trauma, memory, and social marginalization.
-
D.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
E.
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
- 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: Christophe Pélissier Triple: [AJ Auxerre, manager, Christophe Pélissier]
Generated description
Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christophe Pélissier Target entity description: Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
-
A.
Christophe Le Friant
Christophe Le Friant is a French DJ, record producer, and remixer best known under his stage name Bob Sinclar, a prominent figure in the international house music scene.
-
B.
Laurent Chalumeau
Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
-
C.
Laurent Mauvignier
Laurent Mauvignier is a contemporary French novelist known for his psychologically intense, formally innovative works that often explore trauma, memory, and social marginalization.
-
D.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
E.
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd448f08190af425a569d7ed158 |
completed | April 10, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f66856236c8190a70ef287c0146116 |
completed | May 2, 2026, 9:10 p.m. |
| NEDg | Description generation | batch_69f669527fe881909baeb84ccff506c8 |
completed | May 2, 2026, 9:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f669fbb9f88190b0f5cc5bb758d132 |
completed | May 2, 2026, 9:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.