Triple
T25255746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kannada cinema |
E633167
|
entity |
| Predicate | hasNotableProductionHouse |
P14415
|
FINISHED |
| Object | Vajreshwari Combines |
—
|
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: Vajreshwari Combines | Statement: [Kannada cinema, hasNotableProductionHouse, Vajreshwari Combines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProductionHouse Context triple: [Kannada cinema, hasNotableProductionHouse, Vajreshwari Combines]
-
A.
hasNotableCompany
Indicates that an entity is associated with or linked to a company that is considered notable or significant in some context.
-
B.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
C.
hasProductionCompany
chosen
Indicates that an entity (such as a film, show, or media work) is associated with a specific company responsible for its production.
-
D.
hasFictionalProductionCompany
Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
-
E.
ownedProductionCompany
Indicates that one entity previously possessed ownership or controlling interest in a production company.
- 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 21, 2026, 1:13 p.m.