Triple
T27192172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aishwarya (Kannada film) |
E683502
|
entity |
| Predicate | posterFeatures |
P626
|
FINISHED |
| Object | Upendra and Deepika Padukone |
—
|
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: Upendra and Deepika Padukone | Statement: [Aishwarya (Kannada film), posterFeatures, Upendra and Deepika Padukone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: posterFeatures Context triple: [Aishwarya (Kannada film), posterFeatures, Upendra and Deepika Padukone]
-
A.
featuredOn
Indicates that one entity is prominently presented, highlighted, or showcased on or within another entity (such as a platform, publication, or product).
-
B.
featuredFor
Indicates that one entity is highlighted, promoted, or specially showcased in the context or for the benefit of another entity.
-
C.
featuredIn
chosen
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
-
D.
alsoFeatured
Indicates that an entity appears in addition to another primary entity within the same context, work, or presentation.
-
E.
featuresHero
Indicates that something (such as a work, product, or story) prominently includes or centers around a particular hero as a main character or focus.
- 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_69eefad140408190b8586fdebcf9af46 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 9:32 a.m.