Triple
T25234603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalsa |
E632302
|
entity |
| Predicate | hasNotableCameo |
P108137
|
FINISHED |
| Object | Mahesh Babu (voice narration) |
—
|
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: Mahesh Babu (voice narration) | Statement: [Jalsa, hasNotableCameo, Mahesh Babu (voice narration)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCameo Context triple: [Jalsa, hasNotableCameo, Mahesh Babu (voice narration)]
-
A.
cameoCharacter
chosen
Indicates that one entity appears briefly or in a minor, special-guest role within the context or work associated with another entity.
-
B.
hasNotableCrewMember
Indicates that an entity is associated with a crew member who is considered notable or distinguished in some way.
-
C.
hasNotableMultipleAppearances
Indicates that an entity appears multiple times in a context or medium in a way considered significant or noteworthy.
-
D.
hasNotablePersonAsFace
Indicates that an entity is publicly represented or symbolized by a specific notable person, such as a spokesperson, ambassador, or brand face.
-
E.
notableAppearanceIn
Indicates that an entity is prominently featured or plays a significant role in a particular work, event, or context.
- 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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 21, 2026, 1:06 p.m.