Triple
T2315810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imbruvica |
E51059
|
entity |
| Predicate | isContraindicatedWith |
P23156
|
FINISHED |
| Object | strong CYP3A4 inhibitors |
—
|
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: strong CYP3A4 inhibitors | Statement: [Imbruvica, isContraindicatedWith, strong CYP3A4 inhibitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isContraindicatedWith Context triple: [Imbruvica, isContraindicatedWith, strong CYP3A4 inhibitors]
-
A.
hasContraindication
chosen
Indicates that one entity (such as a treatment, drug, or procedure) should not be used or performed in the presence of another entity (such as a condition, factor, or co-medication) because it may cause harm or adverse effects.
-
B.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
-
C.
mayBeComorbidWith
Indicates that two conditions or disorders can occur together in the same individual, potentially influencing each other’s presence or severity.
-
D.
consistentWith
Indicates that one entity does not contradict and is compatible or in agreement with another entity, condition, or set of constraints.
-
E.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.