Triple
T17093047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taï Forest ebolavirus |
E414770
|
entity |
| Predicate | outbreakPattern |
P58390
|
FINISHED |
| Object | no known large human 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: no known large human outbreaks | Statement: [Taï Forest ebolavirus, outbreakPattern, no known large human outbreaks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outbreakPattern Context triple: [Taï Forest ebolavirus, outbreakPattern, no known large human outbreaks]
-
A.
associatedOutbreak
Indicates that one entity (such as a case, location, or event) is linked to or involved in a particular outbreak.
-
B.
outbreakEndYear
Indicates the calendar year in which a particular outbreak is considered to have ended.
-
C.
epidemicType
chosen
Indicates the classification of an epidemic according to its nature, pattern, or mode of spread.
-
D.
associatedWithEpidemic
Indicates that something has a connection or relevance to an epidemic, such as being caused by, occurring during, or contributing to that epidemic.
-
E.
epidemicSpreadFrom
Indicates that an epidemic originates in one location or population and then spreads to another location or population.
- 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.