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KI-Glossar

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Common Sense Reasoning

Ability of a system to infer logical conclusions from non-explicit but universally understood information by humans to solve complex problems.

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Implicit Inference

Process of deducing information that is not directly stated in the input text but is necessary to provide a complete and relevant answer.

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Common Sense Knowledge Base

Organized data structure containing facts, rules, and relationships about the real world, used to power the reasoning of a question-answering system.

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Reasoning Grid

Methodology or framework that breaks down a complex question into simpler reasoning sub-problems, often using common sense knowledge to link the steps.

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Chain-of-Thought

Prompting technique that encourages an AI model to generate the intermediate steps of its reasoning, thereby improving its ability to solve logical and arithmetic problems.

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Semantic Coherence Verification

Mechanism that ensures the generated answer is logically compatible with common sense knowledge and the context provided in the initial question.

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Implicit Knowledge Generation

Ability of a model to create and articulate common sense premises that, although absent from the original text, are essential to justify an answer.

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Common Sense Augmented Language Model

Language model architecture integrated or coupled with a common sense knowledge base, specifically designed to improve performance in implicit reasoning.

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Reasoning Elicitation

Set of techniques aimed at extracting and making explicit the internal reasoning process of an AI model, often to make it more interpretable and reliable.

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Commonsense Knowledge Graphs

Structured representation of commonsense knowledge in the form of nodes (entities) and edges (relations), facilitating logical paths for reasoning.

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Logical Abduction

Form of reasoning that consists of inferring the most plausible hypothesis that can explain a set of observations, widely used to interpret ambiguous situations.

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Qualitative Reasoning

Branch of reasoning that focuses on the symbolic and non-numerical aspects of a problem, manipulating concepts like 'larger', 'hotter', or 'before'.

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Premise Validation

Step in the QA process that checks if the premises (explicit or implicit) on which a question rests are true, false, or undetermined according to commonsense knowledge.

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External Knowledge Integration

Process by which a QA system dynamically merges information from external sources (like commonsense bases) with the question context to enrich its reasoning.

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Reasoning about Causes and Consequences

Application of causal logic to answer questions that link an event to its origins or its future effects, requiring a deep understanding of real-world relationships.

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