Triple
T30362394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yennai Arindhaal |
E772322
|
entity |
| Predicate | leadActorForCharacterSathyadev |
P166850
|
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: [Yennai Arindhaal, leadActorForCharacterSathyadev, Ajith Kumar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacterSathyadev Context triple: [Yennai Arindhaal, leadActorForCharacterSathyadev, Ajith Kumar]
-
A.
roleOfSatyabhama
Indicates that an entity holds or represents the role, position, or character of Satyabhama in a given context or relationship.
-
B.
leadRoleActor
chosen
Indicates that an actor performs a leading or principal role in a work or production.
-
C.
mainActorForCharacterPrabhu
Indicates that the referenced person is the primary actor who portrays the character Prabhu.
-
D.
leadActorOfAdaptation
Indicates that a person is the main actor in a specific adaptation of a work (such as a film, series, or stage version).
-
E.
characterPlayedByShrutiHaasan
Indicates that a specific character is portrayed or acted by Shruti Haasan.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 29, 2026, 7:58 p.m.