Triple
T7906205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Le Bon |
E183582
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Le Bon
Le Bon is a French surname borne by various notable individuals, including actress and filmmaker Charlotte Le Bon.
|
E700147
|
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: Le Bon | Statement: [Charlotte Le Bon, familyName, Le Bon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Bon Context triple: [Charlotte Le Bon, familyName, Le Bon]
-
A.
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
-
B.
Vincent Baudriller
Vincent Baudriller is a French theater director and cultural manager best known for his leadership roles at major European performing arts institutions, including the Festival d’Avignon and the Théâtre de Vidy in Lausanne.
-
C.
Louiguy
Louiguy was a French composer best known for co-writing the iconic chanson "La Vie en rose," popularized by Édith Piaf.
-
D.
Gabriel Le Duc
Gabriel Le Duc was a 17th-century French architect best known for his work on the Val-de-Grâce church and complex in Paris.
-
E.
Benoît
Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
- 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: Le Bon Triple: [Charlotte Le Bon, familyName, Le Bon]
Generated description
Le Bon is a French surname borne by various notable individuals, including actress and filmmaker Charlotte Le Bon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Le Bon Target entity description: Le Bon is a French surname borne by various notable individuals, including actress and filmmaker Charlotte Le Bon.
-
A.
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
-
B.
Vincent Baudriller
Vincent Baudriller is a French theater director and cultural manager best known for his leadership roles at major European performing arts institutions, including the Festival d’Avignon and the Théâtre de Vidy in Lausanne.
-
C.
Louiguy
Louiguy was a French composer best known for co-writing the iconic chanson "La Vie en rose," popularized by Édith Piaf.
-
D.
Gabriel Le Duc
Gabriel Le Duc was a 17th-century French architect best known for his work on the Val-de-Grâce church and complex in Paris.
-
E.
Benoît
Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a5871b8819087ad69c116c40091 |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bc9dfa88190aa5261bdf44823ab |
completed | March 31, 2026, 5:29 a.m. |
| NEDg | Description generation | batch_69cb7633c5a0819089deb6e89d9acb8e |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb84dc86c8190893d67ce07c51aa0 |
completed | March 31, 2026, 12:04 p.m. |
Created at: March 30, 2026, 5:03 p.m.