Triple
T27066990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jhinder Bandi |
E685199
|
entity |
| Predicate | hasDualRoleActor |
P108317
|
FINISHED |
| Object | Uttam Kumar |
—
|
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: Uttam Kumar | Statement: [Jhinder Bandi, hasDualRoleActor, Uttam Kumar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDualRoleActor Context triple: [Jhinder Bandi, hasDualRoleActor, Uttam Kumar]
-
A.
hasAuxiliaryRole
Indicates that an entity serves in a supporting or secondary capacity to another entity or primary role.
-
B.
hasSecondaryProtagonistOccupation
Indicates that a secondary protagonist in a narrative has a specific occupation or job role.
-
C.
hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
D.
combinesRoleOf
chosen
Indicates a relationship where a single entity simultaneously fulfills or merges multiple distinct roles or functions.
-
E.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
- 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_69ef14835fcc81908bd737b4267ae528 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622ea4d9081909696af9f5078f2e9 |
completed | May 2, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:25 a.m.