Triple
T14537304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Force Majeure |
E341080
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | TriArt Film |
E1104470
|
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: TriArt Film | Statement: [Force Majeure, distributor, TriArt Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TriArt Film Context triple: [Force Majeure, distributor, TriArt Film]
-
A.
TriArt Film
chosen
TriArt Film is a Swedish film distribution company known for releasing independent, arthouse, and international cinema.
-
B.
Artina Films
Artina Films is a film production company known for backing notable independent and auteur-driven movies, including Tom Ford’s psychological thriller "Nocturnal Animals."
-
C.
Diaphana Films
Diaphana Films is a French film distribution and production company known for handling acclaimed international and auteur cinema.
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
E.
Brio Films
Brio Films is a French film production company known for producing imaginative and visually distinctive movies such as Michel Gondry’s "Mood Indigo."
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1bb90008190947ac0961393446d |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab414dc8190a233185068cfb8ff |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:22 a.m.