Triple
T28471724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Soccer Association |
E720455
|
entity |
| Predicate | attemptedToPopularize |
P4586
|
FINISHED |
| Object | soccer in the United States |
—
|
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: soccer in the United States | Statement: [United Soccer Association, attemptedToPopularize, soccer in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attemptedToPopularize Context triple: [United Soccer Association, attemptedToPopularize, soccer in the United States]
-
A.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
B.
popularizedBy
chosen
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
C.
popularizedAfter
Indicates that one entity became widely known, accepted, or influential only after another specified entity had already gained popularity.
-
D.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
-
E.
wasPopularBefore
Indicates that one entity enjoyed a higher level of popularity than another during an earlier time period.
- 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64ee2913c8190b0c8ff619b17621b |
completed | May 2, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 2:49 a.m.