Triple
T29732551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thevar Magan |
E752367
|
entity |
| Predicate | awardRecipientForBestSupportingActor |
P8117
|
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, awardRecipientForBestSupportingActor, Sivaji Ganesan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardRecipientForBestSupportingActor Context triple: [Thevar Magan, awardRecipientForBestSupportingActor, Sivaji Ganesan]
-
A.
bestSupportingActorWinner
chosen
Indicates that an entity has received the award for Best Supporting Actor for a particular work or event.
-
B.
bestSupportingActorWinningFilm
Indicates that a film is the one for which an actor won the Best Supporting Actor award.
-
C.
academyAwardForBestSupportingActorYear
Indicates the specific year in which a given Academy Award for Best Supporting Actor was awarded.
-
D.
academyAwardBestSupportingActorNominee
Indicates that a person has been nominated for the Academy Award for Best Supporting Actor in a given year or for a specific film role.
-
E.
bestSupportingActorSeriesMiniseriesOrTelevisionFilm
Indicates that an entity received the award for Best Supporting Actor in a television series, miniseries, or television 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 28, 2026, 7:43 p.m.