Triple
T19992937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebixa |
E494106
|
entity |
| Predicate | drugInteractionCaution |
P68633
|
FINISHED |
| Object | other NMDA antagonists |
—
|
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: other NMDA antagonists | Statement: [Ebixa, drugInteractionCaution, other NMDA antagonists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drugInteractionCaution Context triple: [Ebixa, drugInteractionCaution, other NMDA antagonists]
-
A.
relatedDrug
chosen
Indicates that one drug has a specified relationship or association with another drug, such as interaction, similarity, or therapeutic linkage.
-
B.
associatedWithDrug
Indicates that an entity has a relevant relationship or connection to a specific drug, such as use, exposure, or involvement in its context.
-
C.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
D.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
-
E.
hasContraindication
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.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe2036c8190b9f313215ad44e87 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:31 p.m.