Triple
T24108475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aristada |
E597293
|
entity |
| Predicate | oralOverlapDrug |
P68633
|
FINISHED |
| Object | oral aripiprazole |
—
|
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: oral aripiprazole | Statement: [Aristada, oralOverlapDrug, oral aripiprazole]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oralOverlapDrug Context triple: [Aristada, oralOverlapDrug, oral aripiprazole]
-
A.
hasCommonDrugInteraction
Indicates that two drugs share at least one known interaction that may affect their safety or effectiveness when used together.
-
B.
relatedDrug
chosen
Indicates that one drug has a specified relationship or association with another drug, such as interaction, similarity, or therapeutic linkage.
-
C.
associatedWithDrug
Indicates that an entity has a relevant relationship or connection to a specific drug, such as use, exposure, or involvement in its context.
-
D.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
E.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
- 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_69e288c60f9c8190af948d7354aedbeb |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1de19057c819096a8b3290d33e2f6 |
completed | April 29, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:02 p.m.