Triple
T38475561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyaa Kool Hain Hum |
E915539
|
entity |
| Predicate | leadActorForCharacterKaran |
P191942
|
FINISHED |
| Object | Tusshar Kapoor |
—
|
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: Tusshar Kapoor | Statement: [Kyaa Kool Hain Hum, leadActorForCharacterKaran, Tusshar Kapoor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacterKaran Context triple: [Kyaa Kool Hain Hum, leadActorForCharacterKaran, Tusshar Kapoor]
-
A.
leadActorForCharacterDevdhar
Indicates that the subject is the primary actor who portrays the character Devdhar.
-
B.
leadActorForCharacterKay
Indicates that one entity is the lead actor portraying the character Kay in a given production.
-
C.
leadActorForCharacter Zarak Khan
Indicates that the subject is the primary actor portraying the character Zarak Khan.
-
D.
leadActorForCharacterManorama
Indicates that the subject is the lead actor who portrays the character Manorama.
-
E.
leadActorForCharacterRed
Indicates that an actor is the primary performer portraying the character Red.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69fcef636dfc819085cf91323f2e4edd |
completed | May 7, 2026, 8 p.m. |
Created at: May 3, 2026, 4:31 p.m.