Triple
T25654945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Bengal Rahasya |
E643206
|
entity |
| Predicate | hasComicReliefCharacter |
P71317
|
FINISHED |
| Object | Jatayu |
—
|
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: Jatayu | Statement: [Royal Bengal Rahasya, hasComicReliefCharacter, Jatayu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComicReliefCharacter Context triple: [Royal Bengal Rahasya, hasComicReliefCharacter, Jatayu]
-
A.
isHumorousCharacter
chosen
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
B.
hasLeadComedian
Indicates that one entity serves as the primary or main comedian associated with another entity, such as a show, event, or performance.
-
C.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
D.
hasHumorousSubplotActor
Indicates that an actor participates in or is responsible for a humorous subplot within a larger work.
-
E.
usesInComedy
Indicates that something is employed or incorporated as a humorous element within a comedic context or performance.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 21, 2026, 6:31 p.m.