Triple
T10524038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Blue |
E248249
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Gérard Darmon |
E778599
|
NE FINISHED |
How this triple was built (2 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: Gérard Darmon | Statement: [Betty Blue, hasCastMember, Gérard Darmon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gérard Darmon Context triple: [Betty Blue, hasCastMember, Gérard Darmon]
-
A.
Gérard Darmon
chosen
Gérard Darmon is a French-Moroccan actor known for his distinctive voice and roles in popular French films such as "La Cité de la peur" and "Astérix & Obélix: Mission Cléopâtre."
-
B.
Jean-Pierre Lévy
Jean-Pierre Lévy was a prominent French Resistance leader during World War II, known for organizing and directing clandestine networks against the Nazi occupation.
-
C.
Jean-Pierre Blazy
Jean-Pierre Blazy is a French politician known for serving as the long-time mayor of the suburban Parisian commune of Gonesse.
-
D.
Philippe Habert
Philippe Habert was a French political scientist and commentator known for his work on public opinion and electoral behavior in France.
-
E.
Michel Andrault
Michel Andrault was a prominent French architect known for his influential large-scale housing and urban development projects in the late 20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509e155b08190996325bf484ec55d |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a6efa448190a9d95c5bd68ff34b |
completed | May 2, 2026, 4:46 p.m. |
Created at: April 6, 2026, 12:29 p.m.