Natural Semantic Metalanguage no genetic code of human mind

Anna Wierzbicka, a Polish linguist at the Australian National University, was awarded in 2010 with the International Dobrushin Prize for her research that led to a “Natural Semantic Metalanguage (NSM)”, which according to her is a universal and innate language of all people. With her team, she compared thirteen divergent languages and thus retained all words that could be found with exactly the same meaning. This resulted in a list of 63 words, ranging from logical expressions such as IF and NOT, quantifiers like ONE, TWO and MANY, to verbs such as BE, HAVE, etc. Wierzbicka states in her lecture, “Common Language of All People: The Innate Language of Thought” (2011), that this common vocabulary is a mini-lexicon of elementary semantic primitives or concepts, and contains the rules for an elementary mini-grammar, with which universal meaning is given. Wierzbicka’s work certainly is admirable and of great value for linguistics. But is this metalanguage also a “genetic code of human mind” as she suggest?

Lingua Naturae

Wierzbicka refers to several authors to substantiate her claim on genetic semantics. Umberto Eco explores the probability of a language that is able to eliminate the confusion of tongues in his book “The Search for the Perfect Language”. According to Eco, this language common to all humanity should be rediscovered or invented. Wierzbicka’s main inspiration comes from the mathematician Gottfried Wilhelm Leibniz who lived in the seventeenth century. He wrote the classic work “After Babel”. Leibniz already saw the possibility of a universal semantic system, immediately accessible to everyone regardless of language, which would be based on a set of conceptual primitives. This possibility, according to Leibniz, assumed a human brain that should be standard equipped with a set of simple key concepts, which, by combinations, comprises human thought. Leibniz’s dream of a “Lingua Naturae” was picked up again by the linguist Andrzej Boguslawski, whose work was continued by Wierzbicka. Her NSM would be the realization of Leibniz’ innate mental alphabet, “the alphabet of human thoughts.”

Semantic markers

The foundation of modern semantics was laid in the 20th century. The philosopher and linguist J.J. Katz introduces semantic markers as elementary parts of meaning (Katz & Fodor, 1963). Katz’ markers have meaning within the opposition marked/unmarked. A meaning is the same (synonym) or is the opposite (antonym). “True” is opposite to “untrue”, “even” opposed to “odd” numbers, “light” is set against “dark”. The linguist Geoffrey Leech (1981) says on this subject: “The analysis of meaning value is often considered as parsing the sense of a word in its smallest distinctive features, components that contrast with other components.”

Since the Renaissance, Europeans have pinned down oppositions with the signs + and – (Descartes) or 0 and 1 (Leibniz). In the example: boy = + human – adult + male, the attributes such as ‘human’ and ‘adult’, are called “features”, and the full formula is a “component definition”. Known is the structuralist method of anthropologist Claude Lévi-Strauss. “The contribution of Lévi-Strauss is his assumption that binary opposites are distinctive features within a code, and that they are used as such in ritual scenes and in mythology.” (Leech, 1981).

Wierzbicka’s NSM-list contains some antagonists such as GOOD versus BAD, BIG versus SMALL, LIVE versus DIE. Antonyms that seem to be included purely by chance. The other words do not have antonyms in this list. There is no system of binary oppositions present.

Lexicon and grammar

Wierzbicka seems to assume that meaning is mainly given by the grammatical structures in which words are placed. She regards a common human concept as “not just an isolated semantic element; rather, it constitutes a small lexico-grammatical system“. An elementary wordlist in itself does not have to contain a logical structure of meaning, the structure is given mainly by the grammatical rules.

However, according to Katz & Fodor (1963), a grammatical description of meaning is insufficient. “the interpretation of the sentences is determined in part by the meanings of their morphemes and by semantic relations among the morphemes. The reason for including a dictionary as a component of a semantic theory is precisely to provide a representation of the semantic characteristics of morphemes necessary to account for the facts about sentences and their interrelations that the grammar leaves unexplained.” A semantic structure must already contain a logic in its elementary parts to create unambiguous meaning: “the meaning of a sentence is a function of the meanings of its parts”. The words in the lexicon must consist of semantic markers, which convey the elemental meaning. These markers must be logically connected.

Inner language

An ‘inner’ language, implying a language that each of us standard receives at conception and which is the language of thought, should logically interconnect with the functioning of the nervous system and brain. An inherited language should be present in our genetic material, and carry the genetic code. A semantic notation aiming to refer to an inner, natural, innate language, should contain a mathematical logical structure in line with the functioning of the brain and the nervous system.

Despite Wierzbicka’s reference to mathematics as her main idea behind the empirical investigations, it seems to be missing in her NSM. Perhaps she refers to the form of hierarchy she puts forward in the NSM theory. There are simple concepts which by combination can generate an infinite number of complex ones. The rules for this combining are then given by the grammar, not by a mathematical structure of the lexicon itself. Furthermore, she compares “the elementary concepts with atoms, and the more complex ones, with molecules, as these terms are used in chemistry”. But this draft for a structure is not yet mathematical. Wierzbicka even opposes the natural language to mathematics: “These elementary concepts are the foundation of an innate language, “lingua naturae.” Just as mathematics is, as Galileo said, the language of the physical world, so the innate “lingua naturae” is the language of the inner world, the language of thoughts”.

Orientation Mathematics

The biologist Bogen (1970) states that every higher organism, such as plant, animal or human, originates from a single cell, the fertilized cell. In an organized manner, all information about the building of living creatures is stored in the cell so that it ‘knows’ to what shape it should develop. Investigations were conducted on the growth of bodies from the first cell. “It is the spatial organisation of differentiated cell types that is the essence of pattern formation … The key to the different organization of all these forms does not lie in the cells as such; it lies in how these basic building units are arranged in space development.” The specification of the position in a space presupposes a coordinate system. From observation it appears that “positional information may have an underlying universality.” (Wolpert, cited in Alpaerts, 1982)

The linguist Greimas (1966) discovers that we not only think binary, in antagonists, but also dimensional, according to aspects. He distinguishes three dimensions in the giving of meaning. Depth, height and breadth are dimensions of imaginary but nevertheless meaningful positions and movements. The anthropologist Raymond Firth (1962) discusses the depth (communication), the height (power) and the width (class differences) found in the ceremonies and rituals of ancient cultures. The West African Ndembu classify one hundred words according to three colours: white, red and black (Turner, 1994). The same system we find with the inhabitants of the South Pacific Islands and the indigenous peoples of India, in the Oepanishads (Hume, 1968). The philosopher Martin Heidegger (1970) distinguishes in “What is Metaphysics” depth questions (what?) against height (how?) and breadth questions (why?). The sociologist J.A.A. Van Leent (1972) distinguishes the dimensions of research methods. The research moves in a certain direction, for example, the profound research in the depth dimension. The three parameters of affect “pleasure”, “arousal” and “dominance” from the PAD emotional state model (Mehrabian & Russell, 1974) can also be evaluated in a spatial genetic model.

Dimensions and poles
Fig. 1. Dimensions and poles

The spatial structure is clearly inherent in human thinking. The dimensions in this imaginary space are part of our ability to imagine. Paul Ricoeur (1977) points out the importance of spatial imagery. Thinking is to orient oneself in an imaginary space which determines the direction (dimension) and the sense (0 or 1). The dimensional parameters are the semantic features, their combinations in a formula are the component definitions.

Signals, symbols and emotions

Wierzbicka states her NSM words are “the definitive list of elementary and indispensable human concepts” from Leibniz’s view. He described these primitive concepts as notions which can be understood by themselves, and from whose combinations other more complex concepts arise: “… a set of simple concepts which are as it were ‘letters’ of an innate mental alphabet, and all human thoughts constitute combinations of those simplest concepts”.

Assuming an evolutionary theory of thinking, there must be a biological basis for these concepts that are the building blocks of language, and which make it possible to understand them. Our understanding ability has evolved from an animal signal system that is highly sensory and works with emotions for survival and reproduction. Darwin (1872) sees emotions as adaptations of the organism to typical recurring situations such as danger, death, birth, success …; these are universal and intraspecific inborn. It seems likely that the primitive semantic concepts should be directly based on this sensory and emotional basis.

According to Osvaldo da Pos and Paul Green-Armytage (2007) there is increasing evidence that the link between emotion and expressive language such as image, music, body language, etc. is rooted in human biology, thus enabling the formulation of corresponding rules. These authors have conducted an interesting study. They looked at the relationship between colours and basic emotions and investigated whether Australian and European observers in the same way associated colour with emotional facial expressions. This research differs from others where colours need to be linked to keywords, this was an almost exclusive visual test. They conclude that the association of colours with emotions to a large extent depends on universal biological factors.

Desmet (2002) has researched how emotions are generated by articles of everyday use by their colour, shape and textural qualities. He developed a cross-cultural measuring instrument based on the universal language of facial expression. Desmet states that while emotions are a personal matter, the patterns of the stimulating conditions underlying the emotions are universal. Product emotions can be transformed into values and visualized using ‘product & emotion spaces’ and ‘emotion profiles’.

When looking at the NSM-list we can only determine a very few words referring slightly to an emotion such as GOOD and BAD. Furthermore, there are indeed some words that indicate a sensory sensation such as MANY, BIG, SMALL, FEEL, HEAR, TOUCH, ABOVE, BELOW, FAR, INSIDE. But as one can see, not all human senses are present in this list.

Semantic ability

Scientists increasingly find evidence that there is a genetic code, based on a scientifically substantiated search for a ‘primitive’ language, not in a historical but in a biological sense, which can be explained evolutionarily (Prodi, 1977). Prodi presumes a deep structure that directly underlies the meaning of language expressions. This implies that a human being is born with a basic set of mental hardware and software, instead of a blank slate. A natural set that allows us to communicate with each other; an abstract frame of reference inherited at birth.

Leech (1981) calls it a built-in dictionary, which is part of our mental equipment available to each one of us. Cognitive psychology provides the arguments to make this assumption firm. In his book The Language Instinct (1994), Steven Pinker describes the innate “inner dictionary” as “organized like a thesaurus, so that when one word is found, other similar in meaning are made readily available”. This “mental dictionary” is more than “a long list of items”. “Understanding, requires integrating the fragments gleaned from a sentence into a vast database … Knowledge is not just a list of facts but is organized into a complex network. The language must be structured so that the listener can place each part into an existing framework.” (Pinker, 1994)

For each word, it must be possible to determine the place it occupies in “the long list we call the mental dictionary”. The words are classified in an ordered complex network, a “framework”. This classification is semantic, i.e. the words are arranged according to their meaning “associated with a particular meaning” and connected with other words “similar in meaning”. By placing items in a frame cell, they get a code number, an abstract combination that displays these items. “…some code for representing concepts and their relations in our heads …” (Pinker, 1994). Pinker (2007) shows that the existence of a mental language (mentalese) is necessary. The philosopher Suzanne Langer (1957) formulates the thinking process as follows: “The power of understanding symbols issues in an unconscious, spontaneous process of recognizing the concept in any configuration given to experience, and forming a conception accordingly.” Thinking is according to cognitive psychologists, working with the “mental graphics system”.

It becomes clear that an innate natural language must be more than a number of universally used words with a universally used grammar alone. A universal language contains words that appear in each culture. A natural language refers to the genetic code from which it originates and is much more abstract than the words of the spoken languages. Code also means formula, movement, orientation, hierarchy, tree structures. The natural language emerges as a sort of spreadsheet instead of a glossary with a grammar.

In his study of the perfect language Umberto Eco (1995) distinguishes between a perfect and a universal language, the first being able to render the nature of things and the second being a language that can be spoken by everyone, but that does not have to be perfect. Wierzbicka’s NSM shows the outer manifestation of an ability to understand. The languages that people speak (= culture) use the semantic ability (= nature), but are not the ability themselves. In this sense, NSM more closely aligns with the universal language of Eco. The NSM-list shows only some of the possibilities that exist in the semantic ability, but does not represent the structure necessary to speak of a natural language, or a natural ability.

Genetic semantics

The Belgian semanticist Ferre Alpaerts describes the genetic semantics for the first time in his work “De Denkbeeldige Ruimte” (1981) and “Genetische Semantiek 1 & 2” (1983). He assumes that mental life by evolution emerged from the oldest signs, those of the DNA. “The human ability to use signs is based on applications of genetic encoding. The brain processes sensory, emotional and intellectual stimuli through the same innate code, namely the code of heredity.”

Genetic semantics assumes that the way in which higher organisms process information is derived from the methods used in the cell. “The nervous system and the brain are built up of cells and it seems logical that the way cells exchange signals relies on the genetic code they possess.” From this the proposition emerges that the human signalling system can be traced back to the codons of the DNA.

According to Alpaerts definition of genetic semantics (1983), the innate semantic ability must be structured and encoded corresponding the orientation and circuit mathematics of the DNA. Genetic semantics presents the mental dictionary as a filled up spreadsheet, an active matrix or which not only the cells are numbered but also provided with formulae that are formed by genetic code symbols. Genetic Semantics considers the semantic markers (= semantic features) introduced by J. Katz as ‘letters’ of DNA and combines them in groups of 23 codon ‘words’ of hereditary script (= componential definitions). The system allows a hierarchy of meaning, starting from the abstract level of dimensional semantic markers, into an endlessly refining structure of levels 8, 64, 4096, … The  semantic words refer to the key-images of the mental graphics system. The thinking, i.e. the processing of these system’s concepts, is a creative matter, namely the imagination.

Genetic semantic space
Fig. 2. Genetic semantic space

Research results in different areas of cross-cultural research: cultural psychology, colour psychology, iconography, advertising, all point towards genetic semantics, with antagonists and dimensions as a means of determining and applying universality. Genetic semantics is a useful method because it is based on the congenital processing of sensory and emotional stimuli. Alpaerts compared the results of the research by sociologist Eva Heller (1989) with genetic semantics. Heller’s inquiry reveals that the colours placed with keywords by the respondents in the majority have the same genetic semantic code as the words they are associated with. The conclusions of genetic semantics are thus in many cases the same as Heller’s. Also Oberascher and Gallmetzer (2003) compare their results with those of Heller. “Considerable agreement is shown between our three studies on specific emotional colour-coding, both in relation to each other and in comparison with Heller’s study, as well as between our study and those of others on colour associations”.

Genetic semantic dictionary

The basic principles of genetic semantics make it possible to materialize the semantic ability. Taking into account the biological genetic basis from which this ability has evolved, a model can be drawn. The Semantic Dictionary (SD) of Alpaerts (1991) approaches this goal the closest. Most of the words from the NSM-list have already been given a code in his SD.

Wierzbicka posits that the MSN-list contains words that have a non-reducing semantic meaning, “those concepts which cannot be made clearer by means of definitions”. However, in the genetic semantic model, the semantic markers are located on an even deeper level, namely that of the dimensions (depth, height and breadth) and the poles (0, 1). The word GOOD has the code ‘110’ in the genetic matrix of Alpaerts. GOOD is hierarchically spoken at the 8 level. The 110 code shows the place of the meaning in the spatial model and represents the three dimensions. Emotional dimensions give a parsing of the notion GOOD: pleasurable (depth 1), not-dominating (height 1), and calm (breadth, 0). Opposed in the space is BAD with code ‘001’. The emotional dimensions are: unpleasant (depth 0), dominating (height 0), and aroused (breadth, 1).

Position of the concepts GOOD and BAD in the genetic semantic space
Fig. 3. Position of the concepts GOOD and BAD in the genetic semantic space

Applications of genetic semantics

The potential of Alpaerts’ genetic semantic model is that words get an abstract genetic code formula which makes not only automatic translation easier, but also all sensory experiences such as colour, shape, symbol, sound, music, body posture and movement, facial expression and taste can be connected to each other via their abstract meaning. Synaesthetic relationships between the various human sign systems show possible. This opens enormous possibilities for creative professions such as visual arts, graphic design, music, dance, etc.

In Alpaerts’ SD, for example, The code 110 for the word GOOD from the NSM-list is the same as that of the colour white. In colour psychological dimensions, WHITE analyses as: outer (depth 1), soft (height 1) and passive (breadth 0). Accordingly, the BAD code 001 is the same as for BLACK: inner (depth 1), hard (height 1) and active (breadth 0).

Position of the colours WHITE and BLACK in the genetic semantic space
Fig. 4. Position of the colours WHITE and BLACK in the genetic semantic space

Currently the SD of Alpaerts is transformed into an online relational semantic database called KHNUM. KHNUM aims to be a database of creativity wherein keywords, colours and combinations, shapes, textures, materials, body language, sounds, music, word-sounds, symbols, tastes and their relations, can be searched according to context-related significance and emotional and psychological effect, taking into account cultural aspects. KHNUM is the result of dozens of years of study and scientific research that summarizes the work of anthropologists, philosophers, graphic designers, colour psychologists, artists, advertising experts, sociologists in one concept, classified according to the unique data structure of genetic semantics.

KHNUM links forms of human expression with emotion, psychology, mythology, archaeology, sociology and philosophy. That is why it is a promising application for archiving databases of design, art, music and dance, for the creation and analysing of all human expression, and for developing academic research and approaches to the archive and work of artists and designers in an entirely new way.


According to Wierzbicka, the NSM is the universal and innate language of all people. However, a natural language must be more than a number of universally used words with a universally used grammar only. The following conditions are missing in the NSM list to be able to speak of a “genetic code of human mind”.

  • A system of binary oppositions is missing

Some antonyms are included in the NSM-list, but these oppositions do not form part of an underlying binary lexiconal structure, necessary for giving of meaning.

  • No presence of a logical structure in the list.

A semantic structure must already contain logic in its elementary parts in order to generate unambiguous meaning. The words in the lexicon must consist of semantic markers, which convey the elemental meaning. These markers must be logically connected. This logic is missing in the NSM-list.

  • No natural language

A semantic notation that wants to refer to an inner, natural, innate language, should show how the nervous system and the brain process information. The NSM-list is a summary of words and grammar rules that are common in languages and therefore only constitute the external or cultural manifestation of a natural language or semantic ability.

  • No semantic features

The words in the NSM-list are not primitive semantic concepts which cannot be made clearer by means of definitions. The meaning of the NSM-words can be further divided into semantic markers or features.

  • No clear connection with biology, with senses and emotions

Primitive semantic concepts, as are the words from the NSM-list according to Wierzbicka, must be based on a sensory and emotional foundation, which emerged through evolution. In her list we find only a few words that refer somewhat to an emotion. There are words that indicate sensory sensations, although they represent only a few senses.

  • No genetic semantics

The words get meaning by placing them in a codic abstract structure of which cells are connected by genetic formulas. The coding and formulas should be in accordance to the functioning of the nervous system and brain. To be able to speak of a genetic code of human mind, the natural word list must be structured and encoded according to the orientation and circuit mathematics of the DNA. This genetic basis is completely missing in the NSM-list.

Every culture, every language, uses the innate semantic spreadsheet or semantic ability in her own way. Some cultures will have more or less words for this or that concept. And not all concepts have words in any language. Therefore, merely collecting the words and grammar rules that appear in all languages is not sufficient to expose a genetic semantics. Wierzbicka’s NSM shows only a number of the possibilities present in the human semantic ability, but does not show the structure necessary to speak of a natural language or genetic semantics.

F. Alpaerts & I. Michiels, 2017


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