Triple
T4784607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Kivu Province |
E106444
|
entity |
| Predicate | experiencedEpidemic |
P58388
|
FINISHED |
| Object | Ebola virus disease outbreaks |
—
|
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: Ebola virus disease outbreaks | Statement: [North Kivu Province, experiencedEpidemic, Ebola virus disease outbreaks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: experiencedEpidemic Context triple: [North Kivu Province, experiencedEpidemic, Ebola virus disease outbreaks]
-
A.
epidemicSpreadFrom
Indicates that an epidemic originates in one location or population and then spreads to another location or population.
-
B.
epidemiologicalStatus
Indicates the health-related condition or disease state of an entity within an epidemiological context, such as being infected, susceptible, recovered, or exposed.
-
C.
associatedPandemic
Indicates a relationship where something (such as an event, condition, or entity) is linked or connected to a specific pandemic.
-
D.
publicHealthEmergencyOfInternationalConcern
Indicates that a health event is so serious, sudden, unusual, or unexpected that it poses a public health risk to other countries and may require a coordinated international response.
-
E.
yearOfOutbreak
Indicates the specific calendar year in which an outbreak began or was first identified.
- 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.