Triple
T10291986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | warfarin |
E241385
|
entity |
| Predicate | hasPharmacogenomicAssociation |
P92924
|
FINISHED |
| Object | CYP2C9 polymorphisms |
—
|
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: CYP2C9 polymorphisms | Statement: [warfarin, hasPharmacogenomicAssociation, CYP2C9 polymorphisms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPharmacogenomicAssociation Context triple: [warfarin, hasPharmacogenomicAssociation, CYP2C9 polymorphisms]
-
A.
hasGeneticLocus
Indicates that a genetic feature or trait is located at, or associated with, a specific position (locus) on a genome or chromosome.
-
B.
geneticStatus
Indicates the genetic condition or variant state an entity has in relation to a specific gene or set of genes.
-
C.
hasGeneticAffiliation
Indicates that one entity is genetically related or affiliated with another, such as sharing ancestry, lineage, or genetic characteristics.
-
D.
hasAllele
Indicates that a biological entity possesses or carries a specific allele variant of a gene.
-
E.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d35f048190a215493acdf1f718 |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d29d7cf08190acd70cee634c5cdb |
completed | April 7, 2026, 9:47 a.m. |
Created at: April 6, 2026, 11:42 a.m.