Triple
T23357937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shmoney |
E593100
|
entity |
| Predicate | gainedPopularityOn |
P57498
|
FINISHED |
| Object | social media |
—
|
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 | Statement: [Shmoney, gainedPopularityOn, social media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gainedPopularityOn Context triple: [Shmoney, gainedPopularityOn, social media]
-
A.
gainedProminenceAs
Indicates that an entity became widely recognized or notable in the role, capacity, or identity specified by another entity.
-
B.
gainedProminenceFor
Indicates that an entity became widely recognized or notable specifically because of another entity, action, or achievement.
-
C.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
D.
hasEnduringPopularityOn
chosen
Indicates that something continues to be widely liked, used, or appreciated on a particular platform, medium, or context over an extended period of time.
-
E.
popularizedAfter
Indicates that one entity became widely known, accepted, or influential only after another specified entity had already gained popularity.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a196b308190bfe9bb4b6e7ec363 |
completed | April 29, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:29 p.m.