Triple
T10323055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esther Kahn |
E242687
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Valérie Dréville
Valérie Dréville is a French actress known for her work in both film and theatre, particularly in auteur-driven and art-house productions.
|
E887860
|
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: Valérie Dréville | Statement: [Esther Kahn, hasCastMember, Valérie Dréville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valérie Dréville Context triple: [Esther Kahn, hasCastMember, Valérie Dréville]
-
A.
Valérie Marneffe
Valérie Marneffe is a cunning and manipulative Parisian courtesan in Honoré de Balzac’s novel "La Cousine Bette," known for using her beauty and charm to ruin the men who fall in love with her.
-
B.
Valérie Rojan
Valérie Rojan is known as the partner of French film director Philippe de Broca.
-
C.
Françoise Noguès
Françoise Noguès is a French physician best known as the mother of Brigitte Macron, the First Lady of France.
-
D.
Michèle Méritz
Michèle Méritz was a French actress known for her role in Claude Chabrol’s influential New Wave film "Le Beau Serge."
-
E.
Michèle Mercier
Michèle Mercier is a French actress best known internationally for her role as Angélique in the popular 1960s historical adventure film series of the same name.
- 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: Valérie Dréville Triple: [Esther Kahn, hasCastMember, Valérie Dréville]
Generated description
Valérie Dréville is a French actress known for her work in both film and theatre, particularly in auteur-driven and art-house productions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Valérie Dréville Target entity description: Valérie Dréville is a French actress known for her work in both film and theatre, particularly in auteur-driven and art-house productions.
-
A.
Valérie Marneffe
Valérie Marneffe is a cunning and manipulative Parisian courtesan in Honoré de Balzac’s novel "La Cousine Bette," known for using her beauty and charm to ruin the men who fall in love with her.
-
B.
Valérie Rojan
Valérie Rojan is known as the partner of French film director Philippe de Broca.
-
C.
Françoise Noguès
Françoise Noguès is a French physician best known as the mother of Brigitte Macron, the First Lady of France.
-
D.
Michèle Méritz
Michèle Méritz was a French actress known for her role in Claude Chabrol’s influential New Wave film "Le Beau Serge."
-
E.
Michèle Mercier
Michèle Mercier is a French actress best known internationally for her role as Angélique in the popular 1960s historical adventure film series of the same name.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6cdb6cc8190b37ca4494287128b |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8413f30c8190aebe1504e213b6cc |
completed | April 14, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69de8e6f3fac8190bcd1675978d6d6d7 |
completed | April 14, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de8fa679cc81909cb51035e5403ce9 |
completed | April 14, 2026, 7:04 p.m. |
Created at: April 6, 2026, 11:50 a.m.