Triple
T20449263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Monkey's Mask |
E501602
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | Dendy Films |
—
|
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: Dendy Films | Statement: [The Monkey's Mask, distributor, Dendy Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dendy Films Context triple: [The Monkey's Mask, distributor, Dendy Films]
-
A.
Dendy Films
chosen
Dendy Films is an Australian film distribution company known for releasing independent, arthouse, and international cinema.
-
B.
Nyerai Films
Nyerai Films is a Zimbabwean film production company known for creating socially conscious, women-centered stories under the leadership of writer and filmmaker Tsitsi Dangarembga.
-
C.
Nala Films
Nala Films is an independent film production company known for financing and producing critically acclaimed feature films.
-
D.
Cineyug Films
Cineyug Films is an Indian film production company known for backing major Bollywood projects and entertainment ventures.
-
E.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfffae4819086c727f4143c2737 |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.