Triple
T8008718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panda |
E186428
|
entity |
| Predicate | becameViralHit |
P7687
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Panda, becameViralHit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameViralHit Context triple: [Panda, becameViralHit, true]
-
A.
wentViralOn
chosen
Indicates that content rapidly spread and gained widespread attention or popularity on a particular platform or medium.
-
B.
becameBreakoutHitFor
Indicates that something achieved sudden, widespread popularity or success specifically in relation to a particular entity (such as an artist, brand, or market).
-
C.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
-
D.
musicVideoCameo
Indicates that one entity makes a brief or special-appearance role in the other entity’s music video.
-
E.
socialPhenomenon
Indicates a relationship where an event, behavior, or pattern emerges from and affects interactions within a society or group.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6f76408190a1312369521a187a |
completed | March 31, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:19 p.m.