Triple
T18255452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Hallacy |
E437210
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | machine learning engineer |
C39956
|
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: machine learning engineer Context triple: [Chris Hallacy, instanceOf, machine learning engineer]
-
A.
machine learning researcher
A machine learning researcher is a specialist who develops, analyzes, and improves algorithms and models that enable computers to learn from data and make predictions or decisions.
-
B.
data scientist
A data scientist is a professional who uses statistical analysis, programming, and domain knowledge to extract insights and build predictive models from complex data.
-
C.
machine learning division
The machine learning division is an organizational unit responsible for researching, developing, and deploying data-driven algorithms and models to solve complex problems and enhance products or services.
-
D.
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.
-
E.
machine learning platform component
A machine learning platform component is a modular software element that provides specific functionality—such as data processing, model training, deployment, or monitoring—within an integrated ML lifecycle system.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:34 a.m.