Triple
T9459634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-José Nat |
E228107
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Aurélien Drach
Aurélien Drach is the son of French actress Marie-José Nat and is known primarily in relation to his mother's cinematic legacy.
|
E812812
|
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: Aurélien Drach | Statement: [Marie-José Nat, child, Aurélien Drach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aurélien Drach Context triple: [Marie-José Nat, child, Aurélien Drach]
-
A.
Nicolas Dufourcq
Nicolas Dufourcq is a French business executive known for leading major technology and finance institutions, including serving as chairman of semiconductor company STMicroelectronics.
-
B.
Laurent Merle
Laurent Merle is a French local politician serving as the mayor of the commune of Dolomieu in southeastern France.
-
C.
Grégory Garestier
Grégory Garestier is a French local politician who serves as the mayor of the commune of Maurepas in the Yvelines department.
-
D.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
E.
Nicolas Bérauld
Nicolas Bérauld was a French Renaissance humanist scholar and teacher known for mentoring figures such as the printer and humanist Étienne Dolet.
- 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: Aurélien Drach Triple: [Marie-José Nat, child, Aurélien Drach]
Generated description
Aurélien Drach is the son of French actress Marie-José Nat and is known primarily in relation to his mother's cinematic legacy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aurélien Drach Target entity description: Aurélien Drach is the son of French actress Marie-José Nat and is known primarily in relation to his mother's cinematic legacy.
-
A.
Nicolas Dufourcq
Nicolas Dufourcq is a French business executive known for leading major technology and finance institutions, including serving as chairman of semiconductor company STMicroelectronics.
-
B.
Laurent Merle
Laurent Merle is a French local politician serving as the mayor of the commune of Dolomieu in southeastern France.
-
C.
Grégory Garestier
Grégory Garestier is a French local politician who serves as the mayor of the commune of Maurepas in the Yvelines department.
-
D.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
E.
Nicolas Bérauld
Nicolas Bérauld was a French Renaissance humanist scholar and teacher known for mentoring figures such as the printer and humanist Étienne Dolet.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fc916348190aeb3874a89071677 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189e601508190b116fca9854057bc |
completed | April 4, 2026, 10 p.m. |
| NEDg | Description generation | batch_69d18aee8ef8819080ce061f3d145712 |
completed | April 4, 2026, 10:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18b34d14881909b8da862c12f8727 |
completed | April 4, 2026, 10:05 p.m. |
Created at: March 30, 2026, 7:52 p.m.