Triple
T25454341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veera Simha Reddy |
E637871
|
entity |
| Predicate | leadActorPlaysDualRole |
P32517
|
FINISHED |
| Object | Nandamuri Balakrishna |
—
|
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: Nandamuri Balakrishna | Statement: [Veera Simha Reddy, leadActorPlaysDualRole, Nandamuri Balakrishna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorPlaysDualRole Context triple: [Veera Simha Reddy, leadActorPlaysDualRole, Nandamuri Balakrishna]
-
A.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
-
B.
featuresActorInMultipleRoles
chosen
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
C.
leadActorAlsoDirector
Indicates that the person who plays the lead acting role in a production is also the director of that same production.
-
D.
hasCoProtagonistOccupation
Indicates that two or more co-protagonists share a specified occupation or professional role.
-
E.
creditedRoleOf
Indicates that a particular role or position is formally acknowledged as being held or performed by a specific entity in a credit or attribution 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f723c0688190ada84606ce6be35b |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 2:04 p.m.