Triple
T15974335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hounsfield unit |
E387405
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computed tomography concept |
C36770
|
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: computed tomography concept Context triple: [Hounsfield unit, instanceOf, computed tomography concept]
-
A.
DICOM concept
A DICOM concept is an abstract representation of a medical imaging-related entity, attribute, or relationship defined within the DICOM standard to enable consistent storage, exchange, and interpretation of clinical imaging information.
-
B.
imaging architecture
Imaging architecture is the conceptual and technical framework that defines how imaging components, data flows, and processing pipelines are organized and integrated to capture, transform, analyze, and deliver visual information.
-
C.
imaging survey
An imaging survey is a systematic observational study that captures images of a region of interest—such as the sky, a landscape, or biological tissue—using standardized instruments and methods to enable large-scale analysis and comparison.
-
D.
imaging preparation method
An imaging preparation method is a systematic procedure used to treat, condition, or configure a sample, subject, or environment to enable or enhance the acquisition of meaningful images by an imaging system.
-
E.
medical imaging communication entity
A medical imaging communication entity is a system or component that creates, sends, receives, or processes medical imaging data and related information across healthcare networks.
- F. None of above. chosen
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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
Created at: April 10, 2026, 4:54 a.m.