Triple
T13410251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikita Dragun |
E320066
|
entity |
| Predicate | socialMediaFollowers |
P73542
|
FINISHED |
| Object | millions across platforms |
—
|
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: millions across platforms | Statement: [Nikita Dragun, socialMediaFollowers, millions across platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialMediaFollowers Context triple: [Nikita Dragun, socialMediaFollowers, millions across platforms]
-
A.
socialMediaFollowerCount
chosen
Indicates the number of followers an entity has on a social media platform.
-
B.
followsApproximately
Indicates that one entity follows another in sequence or order, but with some allowable deviation or inexactness in timing, position, or pattern.
-
C.
hasFollowers
Indicates that an entity is followed or subscribed to by one or more other entities.
-
D.
layFollowers
Indicates that one entity is a non-ordained (lay) follower or adherent of another entity, typically a religious figure, institution, or tradition.
-
E.
socialMedia
Indicates a relationship where one entity uses, is associated with, or interacts through social networking or content-sharing platforms with another entity.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:35 p.m.