Triple
T13894424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BlackBerry Messenger |
E334051
|
entity |
| Predicate | becamePopularFor |
P81954
|
FINISHED |
| Object | secure messaging |
—
|
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: secure messaging | Statement: [BlackBerry Messenger, becamePopularFor, secure messaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becamePopularFor Context triple: [BlackBerry Messenger, becamePopularFor, secure messaging]
-
A.
gainedProminenceFor
chosen
Indicates that an entity became widely recognized or notable specifically because of another entity, action, or achievement.
-
B.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
C.
popularizedBy
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
D.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
-
E.
hasEnduringPopularityOn
Indicates that something continues to be widely liked, used, or appreciated on a particular platform, medium, or context over an extended period of time.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a741908190bdf46d76c5f1411a |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.