Triple
T11311019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Problem Solver |
E267834
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | symbolic AI system |
C19367
|
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: symbolic AI system Context triple: [General Problem Solver, instanceOf, symbolic AI system]
-
A.
artificial intelligence
Artificial intelligence is a field of computer science focused on creating systems that can perform tasks that typically require human intelligence, such as learning, reasoning, perception, and decision-making.
-
B.
joint planning and execution system
A joint planning and execution system is an integrated framework that enables multiple agents or stakeholders to collaboratively create, coordinate, and carry out shared plans toward common goals in dynamic environments.
-
C.
intelligence program
chosen
An intelligence program is a software system designed to collect, process, analyze, and interpret data to generate actionable insights or decisions that mimic or support human cognitive capabilities.
-
D.
test of machine intelligence
A test of machine intelligence is a systematic procedure or set of tasks designed to evaluate a machine's ability to exhibit behaviors or problem-solving capabilities that are typically associated with human cognitive processes.
-
E.
knowledge representation framework
A knowledge representation framework is a structured system of formalisms, models, and conventions used to encode, organize, and manipulate information so that it can be interpreted and reasoned about by humans and machines.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
Created at: April 8, 2026, 9:32 p.m.