Triple
T33205233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | probenecid |
E850001
|
entity |
| Predicate | hasDrugInteractionWith |
P149427
|
FINISHED |
| Object | aspirin |
—
|
NE NERFINISHED |
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: aspirin | Statement: [probenecid, hasDrugInteractionWith, aspirin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrugInteractionWith Context triple: [probenecid, hasDrugInteractionWith, aspirin]
-
A.
hasCommonDrugInteraction
chosen
Indicates that two drugs share at least one known interaction that may affect their safety or effectiveness when used together.
-
B.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
C.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
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.
relatedDrug
Indicates that one drug has a specified relationship or association with another drug, such as interaction, similarity, or therapeutic linkage.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:30 a.m.