Triple
T17093029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taï Forest ebolavirus |
E414770
|
entity |
| Predicate | knownHumanCasesCount |
P104742
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Taï Forest ebolavirus, knownHumanCasesCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownHumanCasesCount Context triple: [Taï Forest ebolavirus, knownHumanCasesCount, 1]
-
A.
numberOfSuspectedCases
Indicates the quantity of cases that are believed or suspected to exist but are not yet confirmed.
-
B.
globalCasesEstimate
Indicates an estimated total number of cases of a phenomenon or condition across all regions worldwide.
-
C.
numberOfHospitalized
Indicates the count of individuals who have been admitted to a hospital for medical care.
-
D.
numberOfVictimsConfirmed
chosen
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
E.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfabf548190a0d37bab3d4ef2fa |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d67b14481909fcdbdeaa5c34785 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.