Triple
T34148848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marburg virus |
E875939
|
entity |
| Predicate | firstOutbreakAssociatedWith |
P54330
|
FINISHED |
| Object | imported African green monkeys |
—
|
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: imported African green monkeys | Statement: [Marburg virus, firstOutbreakAssociatedWith, imported African green monkeys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOutbreakAssociatedWith Context triple: [Marburg virus, firstOutbreakAssociatedWith, imported African green monkeys]
-
A.
yearOfOutbreak
Indicates the specific calendar year in which an outbreak began or was first identified.
-
B.
associatedOutbreak
chosen
Indicates that one entity (such as a case, location, or event) is linked to or involved in a particular outbreak.
-
C.
epidemicStartAssociation
Indicates an association between an entity and the onset or initial occurrence of an epidemic event.
-
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.
outbreakDisease
Indicates that a disease begins to spread rapidly within a population or area, marking the start of an 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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:54 a.m.