Triple
T37412516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mycobacterium marinum |
E929610
|
entity |
| Predicate | exposureRiskFactor |
P66795
|
FINISHED |
| Object | aquarium handling |
—
|
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: aquarium handling | Statement: [Mycobacterium marinum, exposureRiskFactor, aquarium handling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exposureRiskFactor Context triple: [Mycobacterium marinum, exposureRiskFactor, aquarium handling]
-
A.
hasRiskFactorFor
Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
-
B.
riskFactorForInfection
chosen
Indicates that something increases the likelihood or susceptibility of an entity to develop a particular infection.
-
C.
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.
-
D.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.