Triple
T1330341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AutoSyringe insulin pump |
E28626
|
entity |
| Predicate | therapyType |
P13744
|
FINISHED |
| Object | insulin pump therapy |
—
|
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: insulin pump therapy | Statement: [AutoSyringe insulin pump, therapyType, insulin pump therapy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: therapyType Context triple: [AutoSyringe insulin pump, therapyType, insulin pump therapy]
-
A.
treatment
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
B.
typeOfRemedy
chosen
Indicates that one entity is a specific kind or category of remedy in relation to another entity.
-
C.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
D.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
E.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c449bc8190acb6603a0ddac7fd |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.