Triple
T29732540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thevar Magan |
E752367
|
entity |
| Predicate | leadActorForCharacterPeriya Thevar |
P166850
|
FINISHED |
| Object | Sivaji Ganesan |
—
|
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: Sivaji Ganesan | Statement: [Thevar Magan, leadActorForCharacterPeriya Thevar, Sivaji Ganesan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacterPeriya Thevar Context triple: [Thevar Magan, leadActorForCharacterPeriya Thevar, Sivaji Ganesan]
-
A.
actorForCharacterThenmozhi
Indicates that an entity serves as the actor portraying the character Thenmozhi.
-
B.
leadRoleActor
chosen
Indicates that an actor performs a leading or principal role in a work or production.
-
C.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
D.
filmLeadCharacter
Indicates that a person or character serves as the primary or central protagonist in a film.
-
E.
mainActorForCharacterPrabhu
Indicates that the referenced person is the primary actor who portrays the character Prabhu.
- 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 28, 2026, 7:43 p.m.