Triple
T9441128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conflans-Sainte-Honorine |
E227646
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
|
E812547
|
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: Laurent Brosse | Statement: [Conflans-Sainte-Honorine, hasMayor, Laurent Brosse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurent Brosse Context triple: [Conflans-Sainte-Honorine, hasMayor, Laurent Brosse]
-
A.
Laurent Barès
Laurent Barès is a French cinematographer known for his work on genre films, particularly in horror and action.
-
B.
Benoît Delhomme
Benoît Delhomme is a French cinematographer known for his visually distinctive work on international films such as The Scent of Green Papaya, The Theory of Everything, and Lawless.
-
C.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
D.
Stéphane Loda
Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
-
E.
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.
- 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: Laurent Brosse Triple: [Conflans-Sainte-Honorine, hasMayor, Laurent Brosse]
Generated description
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laurent Brosse Target entity description: Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
-
A.
Laurent Barès
Laurent Barès is a French cinematographer known for his work on genre films, particularly in horror and action.
-
B.
Benoît Delhomme
Benoît Delhomme is a French cinematographer known for his visually distinctive work on international films such as The Scent of Green Papaya, The Theory of Everything, and Lawless.
-
C.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
D.
Stéphane Loda
Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
-
E.
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.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee4f4a08190ada5ee14fec2b822 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18208ba9081909efa44f98f90c11a |
completed | April 4, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d182ef83e881908a579b6a696ebdc3 |
completed | April 4, 2026, 9:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1836f1be48190a172834ce9eaafe3 |
completed | April 4, 2026, 9:32 p.m. |
Created at: March 30, 2026, 7:50 p.m.