Triple
T30362400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yennai Arindhaal |
E772322
|
entity |
| Predicate | actorForCharacterThenmozhi |
P170210
|
FINISHED |
| Object | Anushka Shetty |
—
|
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: Anushka Shetty | Statement: [Yennai Arindhaal, actorForCharacterThenmozhi, Anushka Shetty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actorForCharacterThenmozhi Context triple: [Yennai Arindhaal, actorForCharacterThenmozhi, Anushka Shetty]
-
A.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
-
B.
mainActorForCharacter_CharlieCrews
Indicates that the referenced person is the primary actor who portrays the character Charlie Crews.
-
C.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
D.
actorForCharacterVictor
Indicates that an entity serves as the actor portraying or performing the character Victor.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- F. None of above. chosen
Provenance (4 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_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 7:58 p.m.