Triple
T29499971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perazhagan |
E748338
|
entity |
| Predicate | leadActressPlaysDualRole |
P32517
|
FINISHED |
| Object | Jyothika |
—
|
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: Jyothika | Statement: [Perazhagan, leadActressPlaysDualRole, Jyothika]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActressPlaysDualRole Context triple: [Perazhagan, leadActressPlaysDualRole, Jyothika]
-
A.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
B.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given work.
-
C.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
-
D.
featuresActorInMultipleRoles
chosen
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
E.
performedInFilmOpposite
Indicates that two performers acted together in significant, often directly interacting roles in the same film.
- 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_69f0bd455a9c8190b40a3e8ea38cf61f |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 28, 2026, 4:22 p.m.