Triple
T25992731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sitara Ghattamaneni |
E646400
|
entity |
| Predicate | celebrityStatusBasis |
P155192
|
FINISHED |
| Object | social media visibility |
—
|
LITERAL FINISHED |
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: social media visibility | Statement: [Sitara Ghattamaneni, celebrityStatusBasis, social media visibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: celebrityStatusBasis Context triple: [Sitara Ghattamaneni, celebrityStatusBasis, social media visibility]
-
A.
fameStatus
Indicates the level or state of public recognition or renown associated with an entity.
-
B.
celebrityMatch
Indicates a relationship where one entity is identified as a suitable or corresponding celebrity counterpart or pairing for another entity.
-
C.
basedOnFameFrom
chosen
Indicates that something is determined, influenced, or derived from the level or source of fame associated with an entity.
-
D.
typeOfPublicFigure
Indicates the specific category or role of public figure that an entity is classified as (e.g., politician, celebrity, activist).
-
E.
knownPrimarilyThrough
Indicates that one entity is chiefly recognized, identified, or made familiar to others by means of another entity (such as a work, role, medium, 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_69e77e88cb8481908da31d4a00661f55 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60549019c81909fb687c81d9ac27d |
completed | May 2, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 22, 2026, 8:57 a.m.