Triple
T19157680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inmazeb |
E468966
|
entity |
| Predicate | riskPopulation |
P18422
|
FINISHED |
| Object | hospitalized patients with Zaire ebolavirus infection |
—
|
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: hospitalized patients with Zaire ebolavirus infection | Statement: [Inmazeb, riskPopulation, hospitalized patients with Zaire ebolavirus infection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskPopulation Context triple: [Inmazeb, riskPopulation, hospitalized patients with Zaire ebolavirus infection]
-
A.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
B.
riskGroup
chosen
Indicates that an entity belongs to a category of individuals or items that share an elevated level of risk relative to others.
-
C.
riskFeature
Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
-
D.
epidemiologicalRisk
Indicates a relationship where one entity poses or is associated with a potential risk of disease occurrence, transmission, or impact to another entity or population from an epidemiological perspective.
-
E.
riskFactorForDeath
Indicates that something increases the likelihood or probability of death occurring.
- 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_69e5eeba91a081909c04d61d6117da06 |
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.