Triple
T22051890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Ripoux |
E544903
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Films 7 |
—
|
NE NERFINISHED |
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: Films 7 | Statement: [Les Ripoux, productionCompany, Films 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Films 7 Context triple: [Les Ripoux, productionCompany, Films 7]
-
A.
Films 7
chosen
Films 7 is a French film production company known for backing movies such as the comedy-thriller "La Totale!".
-
B.
Films 59
Films 59 is a Spanish film production company best known for producing Luis Buñuel’s acclaimed 1961 drama "Viridiana."
-
C.
Flims
Flims is a Swiss alpine resort village in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
-
D.
Movies!
Movies! is an American digital multicast television network specializing in classic and older feature films, typically airing uncut and in their original aspect ratios.
-
E.
Ten Films
Ten Films is a film production company known for producing the movie "Samba."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285513fc8190b691e1f57085956f |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.