Triple
T9841087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRASP Laboratory |
E239226
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computer vision research laboratory |
C26946
|
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: computer vision research laboratory Context triple: [GRASP Laboratory, instanceOf, computer vision research laboratory]
-
A.
machine learning research institute
A machine learning research institute is an organization dedicated to advancing the theory, algorithms, and applications of machine learning through systematic research, experimentation, and collaboration.
-
B.
optics research center
An optics research center is a specialized facility dedicated to advancing the science and technology of light and optical systems through experimental, theoretical, and applied research.
-
C.
cognitive science research center
A cognitive science research center is an interdisciplinary institution that investigates the nature of mind, intelligence, and cognition through collaborative studies in psychology, neuroscience, computer science, linguistics, philosophy, and related fields.
-
D.
computer laboratory
A computer laboratory is a dedicated room or facility equipped with multiple computers and related technologies, providing users with a controlled environment for computing tasks, instruction, and research.
-
E.
optoelectronics research center
An optoelectronics research center is a specialized facility dedicated to studying, developing, and innovating technologies that control and manipulate light and electronic signals for applications such as communications, sensing, and photonic devices.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
Created at: March 30, 2026, 8:33 p.m.