Triple
T22889022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CYP2C19 |
E567681
|
entity |
| Predicate | variationConsequence |
P68444
|
FINISHED |
| Object | poor metabolizer phenotype |
—
|
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: poor metabolizer phenotype | Statement: [CYP2C19, variationConsequence, poor metabolizer phenotype]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: variationConsequence Context triple: [CYP2C19, variationConsequence, poor metabolizer phenotype]
-
A.
variant
Indicates that one entity is an alternative form, version, or variation of another entity.
-
B.
variantScenario
Indicates a scenario that represents an alternative, modified, or derived version of another base scenario.
-
C.
sequenceDifferenceConsequence
chosen
Indicates that a difference or variation in a sequence leads to, or results in, a particular consequence or outcome.
-
D.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
E.
affectsVariant
Indicates that one entity has an influence or impact on a specific variant or version of another entity.
- 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17fc37a448190996e106aacc900f4 |
completed | April 29, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69ef3b6b2e2481908258156937b5a745 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:40 p.m.