Triple
T17114006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magny-les-Hameaux |
E415293
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Bertrand Houillon
Bertrand Houillon is a French local politician who serves as the mayor of the commune of Magny-les-Hameaux in the Île-de-France region.
|
E1352157
|
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: Bertrand Houillon | Statement: [Magny-les-Hameaux, hasMayor, Bertrand Houillon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bertrand Houillon Context triple: [Magny-les-Hameaux, hasMayor, Bertrand Houillon]
-
A.
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.
-
B.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
C.
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
-
D.
Christophe Pélissier
Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
-
E.
Didier Hoarau
Didier Hoarau is a film producer known for his work on the action thriller movie "Taken."
- 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: Bertrand Houillon Triple: [Magny-les-Hameaux, hasMayor, Bertrand Houillon]
Generated description
Bertrand Houillon is a French local politician who serves as the mayor of the commune of Magny-les-Hameaux in the Île-de-France region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bertrand Houillon Target entity description: Bertrand Houillon is a French local politician who serves as the mayor of the commune of Magny-les-Hameaux in the Île-de-France region.
-
A.
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.
-
B.
Matthieu Rougé
Matthieu Rougé is a French Roman Catholic prelate who serves as the bishop of the Diocese of Nanterre.
-
C.
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
-
D.
Christophe Pélissier
Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
-
E.
Didier Hoarau
Didier Hoarau is a film producer known for his work on the action thriller movie "Taken."
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e803ff848190b884fd2c3cc0ee48 |
completed | April 18, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05ad1d53ac81908677f4188fd49cb4 |
completed | May 14, 2026, 11:08 a.m. |
| NEDg | Description generation | batch_6a05aedf05c4819096ac6a61ada4b310 |
completed | May 14, 2026, 11:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05afe523208190a97142cd8e3b887b |
completed | May 14, 2026, 11:20 a.m. |
Created at: April 10, 2026, 5:35 a.m.