Triple
T12763937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legionella |
E305069
|
entity |
| Predicate | riskGroupForDisease |
P18422
|
FINISHED |
| Object | older adults |
—
|
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: older adults | Statement: [Legionella, riskGroupForDisease, older adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskGroupForDisease Context triple: [Legionella, riskGroupForDisease, older adults]
-
A.
riskGroup
chosen
Indicates that an entity belongs to a category of individuals or items that share an elevated level of risk relative to others.
-
B.
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.
-
C.
riskFactorTypeStudied
Indicates that a particular type of risk factor is the subject of study or analysis in a given context.
-
D.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
E.
riskFactorForInfection
Indicates that something increases the likelihood or susceptibility of an entity to develop a particular infection.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8f9f588190bffdea878856204b |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.