Triple
T33205758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ketoconazole |
E850010
|
entity |
| Predicate | hasDrugInteractionMechanism |
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: [ketoconazole, hasDrugInteractionMechanism, CYP3A4 inhibition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrugInteractionMechanism Context triple: [ketoconazole, hasDrugInteractionMechanism, 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.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
C.
mechanismOfActionStudied
Indicates that the relationship involves examining or investigating how an action, intervention, or agent produces its effects or outcomes.
-
D.
hasInteractionEffects
Indicates that one entity’s presence, action, or state alters, influences, or modifies the behavior, effect, or outcome associated with another entity.
-
E.
associatedWithDrug
Indicates that an entity has a relevant relationship or connection to a specific drug, such as use, exposure, or involvement in its context.
- F. None of above. chosen
Provenance (4 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_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e029f0f88190b1f88d82a4a2cabd |
completed | May 3, 2026, 5:42 a.m. |
Created at: May 1, 2026, 1:30 a.m.