Triple
T29333865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naya Aadmi |
E743854
|
entity |
| Predicate | hasProductionStudioStyle |
P30541
|
FINISHED |
| Object | commercial cinema |
—
|
LITERAL 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: commercial cinema | Statement: [Naya Aadmi, hasProductionStudioStyle, commercial cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductionStudioStyle Context triple: [Naya Aadmi, hasProductionStudioStyle, commercial cinema]
-
A.
usesProductionStyle
Indicates that one entity creates, presents, or operates another entity using a particular production style or method.
-
B.
hasRawProductionStyle
Indicates that something is characterized by an unpolished, unrefined, or minimally processed style of production.
-
C.
hasStudio
chosen
Indicates that an entity (such as a film, game, or production) is associated with or produced by a particular studio.
-
D.
hasTheatricalStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular theatrical style associated with another entity.
-
E.
madeInStudioSystem
Indicates that a work was produced under a formal studio system, typically involving centralized control over production, distribution, and creative decisions.
- F. None of above.
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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: April 28, 2026, 1:30 p.m.