Triple
T16876165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merci pour le chocolat |
E421303
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Brigitte Catillon
Brigitte Catillon is a French actress known for her work in film, television, and theater.
|
E1248188
|
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: Brigitte Catillon | Statement: [Merci pour le chocolat, castMember, Brigitte Catillon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brigitte Catillon Context triple: [Merci pour le chocolat, castMember, Brigitte Catillon]
-
A.
Jacqueline Belhomme
Jacqueline Belhomme is a French politician who serves as the mayor of the Paris suburb of Malakoff.
-
B.
Jacqueline Delubac
Jacqueline Delubac was a French actress known for her roles in 1930s French cinema and her collaborations with playwright-filmmaker Sacha Guitry.
-
C.
Catherine Delprat
Catherine Delprat is a French local politician who serves as the mayor of the commune of Écouen in northern France.
-
D.
Yolande Moreau
Yolande Moreau is a Belgian actress, comedian, and filmmaker known for her acclaimed performances in French-language cinema and her distinctive blend of humor and poignancy.
-
E.
Catherine Joubert
Catherine Joubert is a person notable enough to be recognized as a bearer of the surname Joubert.
- 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: Brigitte Catillon Triple: [Merci pour le chocolat, castMember, Brigitte Catillon]
Generated description
Brigitte Catillon is a French actress known for her work in film, television, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brigitte Catillon Target entity description: Brigitte Catillon is a French actress known for her work in film, television, and theater.
-
A.
Jacqueline Belhomme
Jacqueline Belhomme is a French politician who serves as the mayor of the Paris suburb of Malakoff.
-
B.
Jacqueline Delubac
Jacqueline Delubac was a French actress known for her roles in 1930s French cinema and her collaborations with playwright-filmmaker Sacha Guitry.
-
C.
Catherine Delprat
Catherine Delprat is a French local politician who serves as the mayor of the commune of Écouen in northern France.
-
D.
Yolande Moreau
Yolande Moreau is a Belgian actress, comedian, and filmmaker known for her acclaimed performances in French-language cinema and her distinctive blend of humor and poignancy.
-
E.
Catherine Joubert
Catherine Joubert is a person notable enough to be recognized as a bearer of the surname Joubert.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f646308190b5e277b5f51cd315 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232992ec81909dbbd2e28111e8f4 |
completed | May 11, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a0124ce490c81909d5cfd86b7dabb71 |
completed | May 11, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a012569322081908b60694851d50e4b |
completed | May 11, 2026, 12:40 a.m. |
Created at: April 10, 2026, 5:29 a.m.