Triple
T29558328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varalaru |
E749966
|
entity |
| Predicate | featuresTripleRoleBy |
P200146
|
FINISHED |
| Object | Ajith 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: Ajith Kumar | Statement: [Varalaru, featuresTripleRoleBy, Ajith Kumar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresTripleRoleBy Context triple: [Varalaru, featuresTripleRoleBy, Ajith Kumar]
-
A.
featuresActorInTripleRole
chosen
Indicates that a work or production includes an actor who performs three distinct roles within it.
-
B.
featuresDualRole
Indicates that an entity simultaneously fulfills two distinct roles or functions within a given context.
-
C.
featuresDoubleAct
Indicates that an entity includes or presents a performance, show, or act involving two main performers acting together as a pair.
-
D.
roleSynergy
Indicates how effectively two or more roles complement and enhance each other’s performance when combined.
-
E.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
Created at: April 28, 2026, 5:18 p.m.