Triple
T6563401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | fampridine |
E153840
|
entity |
| Predicate | belongsToPharmacologicalGroup |
P24605
|
FINISHED |
| Object | other nervous system drugs |
—
|
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 nervous system drugs | Statement: [fampridine, belongsToPharmacologicalGroup, other nervous system drugs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToPharmacologicalGroup Context triple: [fampridine, belongsToPharmacologicalGroup, other nervous system drugs]
-
A.
hasPharmacologicClass
Indicates that a drug or medicinal product belongs to a specific pharmacologic class based on its mechanism of action or therapeutic effect.
-
B.
drugClass
chosen
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
C.
belongsToGroup
Indicates that an entity is a member of, or is included within, a particular group or collection.
-
D.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
E.
belongsToRegimen
Indicates that something is a component or member of a specified regimen or structured treatment plan.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acf93cb48190b54f5dd6febd34dc |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.