Triple
T3439054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yersinia pestis |
E72523
|
entity |
| Predicate | antibioticClassUsed |
P24600
|
FINISHED |
| Object | aminoglycosides |
—
|
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: aminoglycosides | Statement: [Yersinia pestis, antibioticClassUsed, aminoglycosides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antibioticClassUsed Context triple: [Yersinia pestis, antibioticClassUsed, aminoglycosides]
-
A.
drugClass
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
B.
hasPharmacologicClass
chosen
Indicates that a drug or medicinal product belongs to a specific pharmacologic class based on its mechanism of action or therapeutic effect.
-
C.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
D.
vaccineUsed
Indicates that a particular vaccine has been administered or applied in a given medical or experimental context.
-
E.
administeredWith
Indicates that two or more treatments, drugs, or interventions are given to a patient at the same time or as part of the same therapeutic regimen.
- 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9f6de1481909b789f4b0e1113d3 |
completed | March 8, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69adae00ad588190bef24373b58a2e1a |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:16 p.m.