Triple
T4130714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beard |
E85033
|
entity |
| Predicate | gainedPopularityDuring |
P3813
|
FINISHED |
| Object | 2010s NBA seasons |
—
|
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: 2010s NBA seasons | Statement: [The Beard, gainedPopularityDuring, 2010s NBA seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gainedPopularityDuring Context triple: [The Beard, gainedPopularityDuring, 2010s NBA seasons]
-
A.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
B.
popularizedBy
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
C.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
D.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
E.
popularInPeriod
chosen
Indicates that something is widely liked, used, or influential during a specified 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.