Knowledge Tree
concepts
Also known as: general concepts
Facts (22)
Sources
Sources of Knowledge: Rationalism, Empiricism, and the Kantian ... press.rebus.community 6 facts
claimJohn Locke argues that the ability to form concepts about encountered objects is essential for knowing the world, supplementing the act of sensing.
perspectiveGerman philosopher Immanuel Kant (1724–1804) argues that for perceptions to make sense, they must be received into concepts that already exist within the human mind.
quote“Percepts without concepts are blind and concepts without percepts are empty”
claimThe human mind is equipped from birth with a structure or architecture that enables it to make sense of raw impressions and form concepts where there is no one-to-one correspondence between impressions and ideas.
claimThe presence of general concepts in the human mind suggests that there is not always a one-to-one relation between ideas and corresponding sense impressions, as seen when forming a general concept of the color blue from various instances of blue.
claimA mental representation is defined as including individual concepts (such as the concepts “fire” and “hot”) and the thoughts constructed therefrom (such as “the fire is hot”).
Quantum Approaches to Consciousness plato.stanford.edu Nov 30, 2004 2 facts
referenceGabora and Aerts (2002) described the way in which concepts are evoked, used, and combined to generate meaning depending on contexts.
claimBruza et al. (2015) utilized entanglement-style features in quantum representations of concepts to explain meaning relations and reported initial empirical results.
Empowering RAG Using Knowledge Graphs: KG+RAG = G-RAG neurons-lab.com 1 fact
referenceIn Knowledge Graphs, nodes represent significant entities or concepts such as people, departments, or products, while edges define the relationships or connections between these nodes, such as 'works in' or 'located at.'
Consciousness (Stanford Encyclopedia of Philosophy/Fall 2025 ... plato.stanford.edu Jun 18, 2004 1 fact
referenceS. Yablo authored the article 'Concepts and consciousness', published in Philosophy and Phenomenological Research in 1998.
Epistemology (Stanford Encyclopedia of Philosophy/Fall 2019 Edition) plato.stanford.edu Dec 14, 2005 1 fact
claimAdvocates of the ambiguity response argue that the objection focusing on the word 'know' is misguided because the response only uses the word 'know' at the initial stage before shifting focus to non-linguistic entities like concepts and propositions.
Quantum Approaches to Consciousness plato.stanford.edu Nov 30, 2004 1 fact
referenceGabora and Aerts (2002) contextualize concepts using a mathematical generalization of the quantum formalism in their paper 'Contextualizing concepts using a mathematical generalization of the quantum formalism' published in the Journal of Experimental and Theoretical Artificial Intelligence.
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 1 fact
referenceAl-Aswadi et al. provide a state-of-the-art overview of ontology learning from unstructured text, which aims to identify main concepts and relations for entities within a document collection.
Epistemology - Belief, Justification, Rationality | Britannica britannica.com Mar 13, 2026 1 fact
claimSome empiricists argue that individuals form concepts, such as the concept of red, by mentally abstracting from their experiences of individual items possessing that quality.
Quantum Approaches to Consciousness plato.stanford.edu Nov 30, 2004 1 fact
claimLiane Gabora and Diederik Aerts developed a mathematical generalization of the quantum formalism to contextualize concepts, as published in the Journal of Experimental and Theoretical Artificial Intelligence in 2002.
Epistemology - Stanford Encyclopedia of Philosophy plato.stanford.edu Dec 14, 2005 1 fact
claimThe 'replacement objection' against the ambiguity response—which claims the response focuses on the word 'know' rather than knowledge itself—is misguided because the ambiguity response shifts focus to non-linguistic entities like concepts and propositions after the initial stage.
LLM-empowered knowledge graph construction: A survey - arXiv arxiv.org Oct 23, 2025 1 fact
claimSchema-level fusion is a process that unifies the structural backbone of knowledge graphs, including concepts, entity types, relations, and attributes, into a coherent and semantically consistent schema.
(PDF) Language and Consciousness; How Language Implies Self ... academia.edu 1 fact
claimExperimental methodologies from psycholinguistics are effective for determining the position of specific concepts and word semantics within the hierarchy of meanings and thoughts held by native speakers.
The function(s) of consciousness: an evolutionary perspective frontiersin.org Nov 25, 2024 1 fact
referenceKemmerer (2015) questions whether humans are ever aware of concepts, challenging theories of consciousness such as the global neuronal workspace, integrated information theory, and attended intermediate-level representation.
Understanding epistemology and its key approaches in research cefcambodia.com Jan 21, 2023 1 fact
claimFrom an epistemological perspective, belief is defined as a person's mental representation of an attitude toward ideas or concepts, regardless of whether they are true or false.
Knowledge Graphs: Opportunities and Challenges - Springer Nature link.springer.com Apr 3, 2023 1 fact
referenceDalton et al. (2014) introduced Entity Query Feature Expansion (EQFE), a method that enriches user queries by adding relevant concepts, such as synonyms, using structured attributes and text from a query knowledge graph.
A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Dec 9, 2025 1 fact
imageFigure 10 in the source text illustrates a neuro-symbolic decision stack where raw sensory input is processed by a Neural Perception module into interpretable Concepts, which then feed into a Rules layer to enforce domain-specific logic before a decision is made. The diagram also shows human control channels that allow a domain expert to override or relabel individual concepts, redirect rule evaluation, and critique the Explanation Interface (such as saliency maps, concept heat maps, or rule traces) to refine rule weights and concept classifiers.