Triple
T17093000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebolavirus |
E414769
|
entity |
| Predicate | diseaseOutcome |
P24568
|
FINISHED |
| Object | severe hemorrhagic fever |
—
|
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: severe hemorrhagic fever | Statement: [Ebolavirus, diseaseOutcome, severe hemorrhagic fever]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diseaseOutcome Context triple: [Ebolavirus, diseaseOutcome, severe hemorrhagic fever]
-
A.
survivedDisease
Indicates that an entity successfully lived through and recovered from a specified disease.
-
B.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
C.
outcomeInvolvement
Indicates that an entity is involved in producing, influencing, or being affected by a particular outcome or result.
-
D.
hasPrognosis
chosen
Indicates that one entity (typically a medical condition or case) is associated with an expected course or outcome over time, such as likely progression, duration, or chances of recovery.
-
E.
basedOnDisease
Indicates that something (such as a decision, classification, or action) is determined or derived on the basis of a particular disease or disease-related information.
- 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.