Triple
T19156984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Équateur Province Ebola outbreak |
E468950
|
entity |
| Predicate | probableCases |
P58397
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [2018 Équateur Province Ebola outbreak, probableCases, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: probableCases Context triple: [2018 Équateur Province Ebola outbreak, probableCases, 21]
-
A.
numberOfProbableCases
chosen
Indicates the quantified count of cases that are considered likely or suspected to occur or have occurred, based on available evidence or criteria.
-
B.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
-
C.
numberOfSuspectedCases
Indicates the quantity of cases that are believed or suspected to exist but are not yet confirmed.
-
D.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
E.
knownCasesLinked
Indicates that multiple already-identified cases are connected or related to each other in some meaningful way (e.g., by source, pattern, or chain of events).
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb9cf9081908b17073755e83554 |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.