Triple
T19098023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Fille sur le pont |
E467457
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Claude Aufaure
Claude Aufaure is a French actor known for his work in film, television, and theater.
|
E1410887
|
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: Claude Aufaure | Statement: [La Fille sur le pont, castMember, Claude Aufaure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claude Aufaure Context triple: [La Fille sur le pont, castMember, Claude Aufaure]
-
A.
Etienne Guibourg
Etienne Guibourg was a 17th-century French Catholic priest infamous for his alleged role in black masses and occult rituals during the Affair of the Poisons under Louis XIV.
-
B.
Claude Massot
Claude Massot is an actor known for his role in the French film "Le Soupirant."
-
C.
André Turpin
André Turpin is a Canadian cinematographer and filmmaker known for his visually striking work on acclaimed films such as Denis Villeneuve’s "Incendies."
-
D.
Hugues Aubriot
Hugues Aubriot was a 14th-century French royal official and provost of Paris best known for overseeing the construction of the Bastille fortress.
-
E.
Claude de la Sengle
Claude de la Sengle was a 16th-century Grand Master of the Knights Hospitaller who strengthened the Order’s fortifications on Malta, including founding the fortified city of Senglea.
- 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: Claude Aufaure Triple: [La Fille sur le pont, castMember, Claude Aufaure]
Generated description
Claude Aufaure is a French actor known for his work in film, television, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Claude Aufaure Target entity description: Claude Aufaure is a French actor known for his work in film, television, and theater.
-
A.
Etienne Guibourg
Etienne Guibourg was a 17th-century French Catholic priest infamous for his alleged role in black masses and occult rituals during the Affair of the Poisons under Louis XIV.
-
B.
Claude Massot
Claude Massot is an actor known for his role in the French film "Le Soupirant."
-
C.
André Turpin
André Turpin is a Canadian cinematographer and filmmaker known for his visually striking work on acclaimed films such as Denis Villeneuve’s "Incendies."
-
D.
Hugues Aubriot
Hugues Aubriot was a 14th-century French royal official and provost of Paris best known for overseeing the construction of the Bastille fortress.
-
E.
Claude de la Sengle
Claude de la Sengle was a 16th-century Grand Master of the Knights Hospitaller who strengthened the Order’s fortifications on Malta, including founding the fortified city of Senglea.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36b279c819091a8d51f044bc644 |
completed | April 20, 2026, 8:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0826f137a88190ad9961718b77d0c3 |
completed | May 16, 2026, 8:12 a.m. |
| NEDg | Description generation | batch_6a0827c6a68c8190aed2d531b4fd2030 |
completed | May 16, 2026, 8:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08288d98fc8190a146f43a027682f0 |
completed | May 16, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:04 p.m.