Triple
T19411509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalgona challenge |
E485597
|
entity |
| Predicate | timeOfViralSpread |
P135773
|
FINISHED |
| Object | 2021 |
—
|
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: 2021 | Statement: [Dalgona challenge, timeOfViralSpread, 2021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfViralSpread Context triple: [Dalgona challenge, timeOfViralSpread, 2021]
-
A.
epidemicSpreadFrom
Indicates that an epidemic originates in one location or population and then spreads to another location or population.
-
B.
spreadingStatus
Indicates the current state or progression of how something is spreading or being disseminated (e.g., whether and how it is expanding, stable, or declining).
-
C.
timePeriodOfMajorOutbreak
Indicates the time span during which a major outbreak occurred or was most active.
-
D.
isViral
Indicates that something spreads rapidly and widely through a population or network, often via person-to-person or user-to-user transmission.
-
E.
epidemicScale
Indicates that an event, condition, or phenomenon occurs with such widespread prevalence and rapid spread that it reaches an epidemic level in scale.
- F. None of above. chosen
Provenance (4 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af681288190ba2ec52d5adb6a22 |
completed | April 20, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:37 p.m.