Triple
T38637017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loop app |
E937592
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | do-it-yourself artificial pancreas system |
C59203
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: do-it-yourself artificial pancreas system Context triple: [Loop app, instanceOf, do-it-yourself artificial pancreas system]
-
A.
insulin pump
An insulin pump is a wearable medical device that delivers precise, continuous doses of insulin to help people with diabetes manage their blood glucose levels.
-
B.
diabetes treatment device
A diabetes treatment device is a medical tool or system designed to monitor blood glucose levels and/or deliver therapies such as insulin to help individuals manage and control their diabetes.
-
C.
diabetes management software
chosen
Diabetes management software is a digital tool that helps individuals and healthcare providers monitor blood glucose, track medications and lifestyle factors, analyze trends, and support treatment decisions to better control diabetes.
-
D.
life support control device
A life support control device is a system that monitors and regulates critical environmental and physiological parameters—such as oxygen levels, temperature, pressure, and humidity—to maintain safe, stable conditions necessary for sustaining human life.
-
E.
modular instrumentation platform
A modular instrumentation platform is a flexible, scalable system that integrates interchangeable measurement and control modules into a common hardware and software framework to build customized test, monitoring, or automation solutions.
- F. None of above.
Provenance (1 batch)
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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:32 p.m.