Triple
T9432578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rickey Thompson |
E227417
|
entity |
| Predicate | hasSocialMediaFollowing |
P73542
|
FINISHED |
| Object | millions of followers 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 of followers across platforms | Statement: [Rickey Thompson, hasSocialMediaFollowing, millions of followers across platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocialMediaFollowing Context triple: [Rickey Thompson, hasSocialMediaFollowing, millions of followers across platforms]
-
A.
hasFollowers
Indicates that an entity is followed or subscribed to by one or more other entities.
-
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.
hasSocialEngagement
Indicates that an entity participates in or maintains some form of social interaction, activity, or relationship with others.
-
D.
socialMediaFollowerCount
chosen
Indicates the number of followers an entity has on a social media platform.
-
E.
hasMajorFollowingAmong
Indicates that the subject is widely popular or influential within the specified group or audience.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e61a114819081fc4a2ad39c96ba |
completed | April 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:49 p.m.