Triple
T4784854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 Équateur Province Ebola outbreak |
E106450
|
entity |
| Predicate | likelyZoonoticOrigin |
P40200
|
FINISHED |
| Object | contact with infected wildlife |
—
|
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: contact with infected wildlife | Statement: [2017 Équateur Province Ebola outbreak, likelyZoonoticOrigin, contact with infected wildlife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: likelyZoonoticOrigin Context triple: [2017 Équateur Province Ebola outbreak, likelyZoonoticOrigin, contact with infected wildlife]
-
A.
zoonoticPotential
chosen
Indicates the potential for a disease or pathogen to be transmitted from animals to humans.
-
B.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
-
C.
isReservoirOf
Indicates that one entity serves as a storage source or container holding a particular substance, resource, or quantity for another entity or purpose.
-
D.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
E.
associatedOutbreak
Indicates that one entity (such as a case, location, or event) is linked to or involved in a particular outbreak.
- 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_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. |
Created at: March 20, 2026, 1:22 p.m.