Triple
T12509638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olivier |
E299040
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Olivier Latry
Olivier Latry is a renowned French organist and improviser, best known as one of the titular organists of Notre-Dame Cathedral in Paris.
|
E994241
|
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: Olivier Latry | Statement: [Olivier, hasNotableBearer, Olivier Latry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivier Latry Context triple: [Olivier, hasNotableBearer, Olivier Latry]
-
A.
Laurent Chalumeau
Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
-
B.
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.
-
C.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
D.
Olivier Basselin
Olivier Basselin was a 15th-century French poet and songwriter from Normandy, known for his drinking songs and influence on the tradition of French popular poetry.
-
E.
Olivier Bernet
Olivier Bernet is a French composer best known for his film scores, particularly his collaborations on animated and genre films.
- 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: Olivier Latry Triple: [Olivier, hasNotableBearer, Olivier Latry]
Generated description
Olivier Latry is a renowned French organist and improviser, best known as one of the titular organists of Notre-Dame Cathedral in Paris.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Olivier Latry Target entity description: Olivier Latry is a renowned French organist and improviser, best known as one of the titular organists of Notre-Dame Cathedral in Paris.
-
A.
Laurent Chalumeau
Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
-
B.
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.
-
C.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
D.
Olivier Basselin
Olivier Basselin was a 15th-century French poet and songwriter from Normandy, known for his drinking songs and influence on the tradition of French popular poetry.
-
E.
Olivier Bernet
Olivier Bernet is a French composer best known for his film scores, particularly his collaborations on animated and genre films.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541c1ca08190a4026c394ebcbeb5 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6685bafcc8190beae748d979762e1 |
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_69f669fe4bc48190adba50ad58b10c45 |
completed | May 2, 2026, 9:17 p.m. |
Created at: April 8, 2026, 9:57 p.m.