Triple
T4784670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuhovi |
E106446
|
entity |
| Predicate | epidemicImpact |
P58389
|
FINISHED |
| Object | heavily affected locality during the 2018–2020 Kivu Ebola epidemic |
—
|
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: heavily affected locality during the 2018–2020 Kivu Ebola epidemic | Statement: [Vuhovi, epidemicImpact, heavily affected locality during the 2018–2020 Kivu Ebola epidemic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epidemicImpact Context triple: [Vuhovi, epidemicImpact, heavily affected locality during the 2018–2020 Kivu Ebola epidemic]
-
A.
covid19Impact
Indicates the effect, consequences, or influence that COVID-19 has on a given entity, condition, or situation.
-
B.
epidemicSpreadFrom
Indicates that an epidemic originates in one location or population and then spreads to another location or population.
-
C.
epidemiologicalStatus
Indicates the health-related condition or disease state of an entity within an epidemiological context, such as being infected, susceptible, recovered, or exposed.
-
D.
associatedPandemic
Indicates a relationship where something (such as an event, condition, or entity) is linked or connected to a specific pandemic.
-
E.
epidemiology
Indicates the study and analysis of how diseases or health-related conditions are distributed and spread within populations, and the factors influencing these patterns.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ae49ec81908f16248d22d1155f |
completed | March 20, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69bd622e1b408190806c15c61519fc74 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:22 p.m.