Triple
T33205819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | itraconazole |
E850011
|
entity |
| Predicate | hasSignificantDrugInteractionVia |
P176408
|
FINISHED |
| Object | CYP3A4 inhibition |
—
|
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: CYP3A4 inhibition | Statement: [itraconazole, hasSignificantDrugInteractionVia, CYP3A4 inhibition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantDrugInteractionVia Context triple: [itraconazole, hasSignificantDrugInteractionVia, CYP3A4 inhibition]
-
A.
hasCommonDrugInteraction
Indicates that two drugs share at least one known interaction that may affect their safety or effectiveness when used together.
-
B.
hasDrugInteractionMechanism
chosen
Indicates that one substance affects another through a specific biological, chemical, or pharmacological mechanism that alters its drug action or effects.
-
C.
hasNotableDrug
Indicates that an entity is associated with a drug that is considered notable or significant in some recognized context.
-
D.
associatedWithDrug
Indicates that an entity has a relevant relationship or connection to a specific drug, such as use, exposure, or involvement in its context.
-
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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: May 1, 2026, 1:30 a.m.