Triple
T29314598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janhvi Kapoor |
E743343
|
entity |
| Predicate | worksPrimarilyIn |
P148956
|
FINISHED |
| Object | Hindi cinema |
—
|
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: Hindi cinema | Statement: [Janhvi Kapoor, worksPrimarilyIn, Hindi cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksPrimarilyIn Context triple: [Janhvi Kapoor, worksPrimarilyIn, Hindi cinema]
-
A.
workedPrimarilyIn
chosen
Indicates that an entity carried out the majority of its work, activity, or career within a particular field, location, or context.
-
B.
workedPrimarilyOn
Indicates that an entity devoted the majority of its work, effort, or activity to a particular project, field, or subject.
-
C.
workAt
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
D.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
-
E.
worksNear
Indicates that one entity performs its work or duties in close physical proximity to another entity.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 28, 2026, 1:19 p.m.