Triple
T2924493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turing test |
E78810
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | test of machine intelligence |
C13032
|
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: test of machine intelligence Context triple: [Turing test, instanceOf, test of machine intelligence]
-
A.
game-playing AI
A game-playing AI is an artificial intelligence system designed to analyze game states, make strategic decisions, and execute actions to achieve optimal performance or victory within a defined set of game rules.
-
B.
robot
A robot is an autonomous or semi-autonomous machine capable of sensing its environment, processing information, and performing physical or virtual tasks, often programmable to adapt to different functions.
-
C.
model-based reinforcement learning algorithm
A model-based reinforcement learning algorithm is a decision-making method that learns or uses an explicit model of the environment’s dynamics to plan and select actions that maximize long-term rewards.
-
D.
landmark paper in machine learning
A landmark paper in machine learning is a highly influential publication that introduces foundational theories, algorithms, or empirical results that significantly shape subsequent research and practice in the field.
-
E.
image recognition model
An image recognition model is a computational system that analyzes visual input to automatically identify, classify, and sometimes localize objects, patterns, or features within images.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
Created at: March 8, 2026, 2:55 p.m.