Triple
T22871199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | thioridazine |
E567199
|
entity |
| Predicate | hasTherapeuticUse |
P40313
|
FINISHED |
| Object | treatment of schizophrenia |
—
|
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: treatment of schizophrenia | Statement: [thioridazine, hasTherapeuticUse, treatment of schizophrenia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTherapeuticUse Context triple: [thioridazine, hasTherapeuticUse, treatment of schizophrenia]
-
A.
potentialTherapeuticUse
Indicates that something is being considered or investigated as a possible treatment or therapy for a condition or disease.
-
B.
medicinalUse
chosen
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
C.
hasTherapeuticGoal
Indicates that an action, treatment, or intervention is undertaken with the intention of achieving a specific therapeutic or health-related outcome.
-
D.
hasPediatricUse
Indicates that something is intended, approved, or suitable for use in children or pediatric contexts.
-
E.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f04b06481909004818ec8fc5a26 |
completed | April 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:38 p.m.