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The Quadranym Model of Word-Sensibility (Q): An Ecological Systems Perspective On Word-Level-Concepts & Contextual Unitizations – Non-Mental-Representation Representation – Design Before Define Approach.

Q: A method to analyze and cluster words – an ontological alignment system to represent dynamic word relations in units, scripts and layers.

Theories Behind The Approach (cited): posts.

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We aim to explore the dynamic roles that words can play in the acquisition of commonsense for machine learning. We begin with the question, how much information about the world does a word pack? Perhaps it’s an odd question but consider that words play a fundamental role in the way we interconnect in the world that we all interact in, while conversely our interactive behaviors yields our word sense dynamics. In a basic lexical ontology a link between a concept in the ontology and the meaning of the lexical unit is essentially an analytical mapping between a collection of word senses. Development and change is inherent in how we relate to each other. How can our word sense dynamics be better represented in an ontology? A dynamical systems perspective is conceptually provided.

Unpacking Words: Q Analysis

Our perspective begins with a distinction in the contextualizing of word sense. A Situational Context is the communicative ability to present or understand the objective circumstances in which an event occurs. We introduce the idea of a Dynamical Context, it is something different from a Situational Context and can be summarized as follows:

• Dynamical Context: a situation resonates with a preexisting psychology, a predetermined expectation for behavior within that situation, and produces a synergy response, reshaped for the moment.
• Dynamical Contextual Systems: possibly comprising many dynamics or areas any of which could be subject to a discreet dynamic situation, in which all of them may interpenetrate or interact or relate to one another.

The aim of this introduction is to illustrate how dynamical and situational contextual analyses can compliment one another in a knowledge base system. The dynamical contexts (Q system) involves conceptual matrices that revolves around two basic components that we will now introduce:

• Quadranyms represent autogenously unitized contextual dimensions.
  
• Polynyms represent strategically divided contextual dimensions

In the Q ontology, words play a primary role in illustrating how confluential thought emerges through our behaviors and interactions as dynamic contextual units or Q-units. Q-units optimally and concisely frame topics of experience. The Q-unit is a hypothetical explanatory construct to intervene with the notion of word-sensibility. The approach is generally aligned with enactivism.

• Cognition emerges in the interaction between an organism and the environment. (Hutto D., Myin E., et al 2013)
  

• Q-units: Quadranyms are any four terms that represent the four dimensions of the Q-unit. Q-units are frameworks that can apply various schematics to words and topics and can be linked together to form scripts. Basically, Q-units represent concise and optimal heuristic frameworks for experiential myths i.e., stories about experience.

Context plays an enormous role in language understanding, however, the relationship between context and language is still under debate.

• “The controversy begins with the question of how much in language and which parts of it are context-dependent, but it also, and perhaps more substantially, includes the question of how the relationship between language and context should be conceptualized in more theoretical terms”. (Auer 1995)
  

In word-sensibility representations, commonsense experiences illustrate interactive dynamical dimensions between dynamical contexts and situational contexts. The tension between contexts begins at the immanent standpoint of the interaction, the actual dynamical context. To then have a complete sense requires a situational context. The term situational refers to the objective potentials available to the dynamical context. For instance, if hungry is the dynamical context, then it follows that food is a situational context and any inference to food will also apply to the dynamic of hungry.

The Q-unit is an analytical tool that explores the dynamic variations of a topic. Consider the word eat. In this variation, notice how Sate(food) are in the world sense and Starve(hungry) are in the self sense. The Q-unit’s various schematics allows quick inferences between content, in this case, food is in world, hungry is in self. Quadranyms are nested notions of this sort.

• The Q-unit acts as a kind of deictic center for a contextual trace in relation to which a word sense is to be interpreted. 

We refer to polynyms and quadranyms as polyordinates: a particular number of situationally related superordinate terms over clusters of subordinates.

Q-units are populated by, quadranyms: four superordinate related words of a topic, each represents a dimensional cluster of subordinates.

Subordinate cluster: {…}

Q-unit category/contextualization appears in brackets:

• (∀x) eat(x) ⟹ [Sate{…}(hungry{…}) ⊇ Starve{…}(food{…})(x)]

Q-units are the subjects of polynyms. A Polynym is a set of predicates of any number (usually a small number) that often appear together and can be used as a contextual-topic, for instance, of Social Domain in 5 Dimensions:

As in.“Jan and Stan want to take us out to eat!”

1. Eat(x)
2. Dinner(x)
3. Restaurant(x)
4. Friends(x)
5. Fun(x)

Dynamical & Situational: There are two levels of analyses to the Q, the inter-subjective analysis involving  semantic networks, situational contexts or objective fields, and the intra-subjective analysis involving Q-units, responsiveness and dynamical contexts. The Q focus of analysis zooms in on the subjects of predicates. Here, the analysis pertains to the anchorage of subjects, topics or word senses of the polynym or situational context.

Quadranyms represent certain topical orientations that may or may not apply to an image schema depending on the polynym (set of predicates). Polynyms are important factors to help trigger which quadranym topic is best suited. Consider the Quadranym topics for eat as fashioned below.

1. Eat(x)

• (∀x) eat(x) ⟹ [Sate(hungry) ⊇ Starve(food)(x)]
• (∀x) eat(x) ⟹ [Intact(chew) ⊇ Fragment(substance)(x)]
• (∀x) eat(x) ⟹ [Available(consume) ⊇ Deplete(resource)(x)]
• (∀x) eat(x) ⟹ [Stable(corrode) ⊇ Disintegrate(substance)(x)]
• …

There is a lot to unpack in the examples above. As we will see later, the different topics are aligned in a matrix and can be nested with other topics. Next, we will illustrate the basic theoretical methods and perspectives.

Each bracket is a class of two propositional sets:

1. Superset: dynamical-proposition
2. Subset: situational-proposition

• [dynamical-proposition ⊇ situational-proposition].

As we will see in the Q Model Introduction later, the division between dynamical and situational set categories are referred to as hemispheres – each hemisphere is its own ontology.

1. Dynamical: Subjective Sense Ontology
2. Situational: Objective Sense Ontology

The dynamical-situational divide in a word sense does not represent a true dichotomy as both sides are categorically dynamical. However, they are two separate distribution processes of a word sense, each a subsuming process forming content clusters to be distributed. The system’s process involves procedural scripts, each frame of a script is a Q-unit. Q-units form scripts while polynyms form layers of scripts able to run simultaneously.

• Polynyms run on different timelines, from over arching to ocurrent times.

As we will see later, each set is represented by a different categorical Role, the coherent role and the conditional role. In other words, although the superset contains all the content, the subset is a potential, an exclusive class of conditions that tie to particular situational contexts.

In Q systems, content forms attended/unattended dynamical categories. To generalize the attended/unattended dynamic, lexical content systematically re-aligns through a feedback loop in a correspondence with Q Roles. These are categorical roles that pertain to the interactions of an agent-environment relationship. An effective description of this process can be illustrated as nested dynamical systems. (Chemero, 2009)

• Blind people who are experts at navigating with their cane don’t experience their cane, they experience the world at the end of their cane (Merleau-Ponty, 1944).

In our model, the cane begins as an object of one’s objective field (slide 1.1), and then when in use, the cane realigns as a zero point of reference becoming categorically actual sense. The zero point cane takes aim at the world point of reference that is categorically potential sense. The cane is no longer true or false. The world begins the attended dimension where truth conditions can populate one’s objective field (i.e., information about the world). In this way Q Roles, as we will further illustrate later, oscillate between actual and potential categorical systems to generate scripts.

For example…

• navigate ⇒ world:<find>:[Actual(self) ⊇ Potential(world)]<find>[Actual(world) ⊇ Potential(navigate)]<find>[(Actual(navigate) ⊇ Potential(cane)]<find>[Actual(cane) ⊇ Potential(world)]<stop>

System 1 & System 2: Consider the illustration above, the Q-unit (meta-frame system) is about pulling in, filtering and generalizing the objective field (deliberative frame system).

• Generally, the Q-unit representation is toward normative claims where the objective field is toward descriptive claims.

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From: Overview

System Description: The Q model is a method and theory of commonsense representation that pertains to motivated dynamical contexts anchoring word-level concepts, we refer to it as word sensibility. The Q is concerned with the interactivity between nested contextual units. At its core, a word sensibility is that which prescribes internal and external distinctions to contextual units. Various metaphysical notions apply, such as, part/whole, plurality/unity, being/becoming, time and space. The model’s approach toward these notions requires methods of description that scale different levels of thoughts/resources, attended and unattended. All of it attempts to look at how contextual constructs make impressions on our choices – our sense making. Although it is itself an ontology, it’s most practical application might be best suited as a supplement for lexical ontologies designed for natural language processing. Essentially, it is a hybrid between a lexical ontology and a commonsense knowledge base. Basic goals include, improving tractability, heuristics and commonsense knowledge data.

• Q-units are dynamic frameworks for specified terms.

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Interface:

The Q-unit is a tool to help with word analysis. Human operators become familiar with the Q method of analysis. Operators monitor and assess the system’s content. Quadranyms can be acquisitioned in a number of ways. Below is a basic human Interface. Interfaces can be made into games to make the process easier and more compelling for public participation.

Like quadranyms, polynyms can also be collected. Many polynyms already exist in the world since they represent any number of dimensions for strategic thinking. For example, Freud’s polynym (p3) , Psyche: Id, Ego, Superego. It is used as a strategy to understand the human mind.

Quadranyms and polynyms, as we will show in future works, belong to a kind of thesaurus that collects sets of word dimensions that are generally regarded as strategic ways of thinking. Our hope is that once quadranyms and polynyms are better understood their practical and diverse applicability will be apparent. How these and other factors help provide a dynamical systems perspective on how word senses are anchored to word-sensibility systems and processes is what we will continue to explore.

Q Theory of Content:

A lexicon like wordnet defines a word (with gloss and synsets) for as many distinct senses in the entry. The information content of the word’s general message will at times pertain to the different senses in some manner. Humans quickly perceive the various correlations between the senses. What kind of framework can be used for this kind of analysis? Researchers are discovering that the mind responds to written text using many of the same resources used to interact in the world. Frameworks for analyzing what the mind is doing with these resources while reading text is easier to apply when it pertains to sentential sources then when to word sources. The systematicity of words seems to exist in the dynamic between us and those things we resonate with in the world. Words are what humans do naturally, dynamically respond to things. The idea of words as being atomic content of sentences does not suit the implications of this kind of analysis.

• We mean the term Sensibility as, “a responsiveness toward something. What we mean as word-sensibility is, a responsiveness toward a topic, by which a unitization of other-separate topics is cued, in which the unit effect is a capacitance to aptly elect the probable truth conditions for that topic.

A Q-unit acts like a kind of capacitor that when plugged into a circuit stores topical word-sensibility information.

We generally describe Word Sensibility as a dynamic between what is coherent and what is conditional. The Q-unit is a recursive process based on variations of these principles.

The Coherent Bias: Any time we speak of a coherent sense in terms of the Q model, we speak of a bias toward certain conditions.

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Consider the phrase, Eat bird. We will revisit this phrase through out. Each word is its own unit, what do we know about these units? Our experiential senses learns to parse between what is necessary and what is possible in terms of our interactions with the world when reading. It is more than just knowing if bird is to eat or be eaten, that can be syntactically understood and doesn’t require our experiential senses. In our approach, a basic experiential dynamic is involved in every word. In Q analysis, to be categorized as objects of experience depends on the interactivity between what is coherently actual and what is conditionally potential. This is a dynamic that is basically the same if one simply thinks of bird or thinks of eat or when thought of together. This dynamic represents a unit of context used to abstract the mind simulating perceptual and motor systems that are then applied to the textual world we’re immersed in. The coherent and conditional principles help guide the systems choice of dynamical content.

• The coherent sense of a Q-unit is always more experience necessary. More experience necessary is the dynamic reason for the coherent sense. In a dynamical context, the coherent sense is not a result but an attribute. Blocking the attribute means confusion, unconsciousness or unwillingness to move forward. No more experience necessary is simply the potential of the coherent sense. The conditional sense is that potential, and when found that is no more experience necessary. The coherent sense doesn’t then resolve, rather, it becomes something different.
  

Consider how some interactions with the world might feel coherent to our sense of responsive self while other interactions might feel conditional to our sense of responsive self. For instance, say you come across a tool and you have no idea what it is for, the tool is a condition that requires your coherent sense to have more experience. The tool feels conditional, it depends on a new coherent. Now, for the expert of that tool, the condition that is the tool, is no more experience necessary. The experts coherent sense of the tool is easily found and has established responses to its associated conditions. The neophyte must access analogous kinds of coherent senses. What is abstracted in the Q is the coherent core that is necessary before the mind can reach for ways to respond to any condition. The idea is to resolve the issues between coherent and conditional senses. Simply focusing on a word enacts the process. We describe the process dynamically; a virtual oscillation between the two senses.

“I know nothing in the world that has as much power as a word. Sometimes I write one, and I look at it, until it begins to shine.” –– Emily Dickinson

Words are resources to the Q system used to help decode an agents dynamical interaction with its environment. The Coherent sense is an attribute that plays a specific role in this process, it is an attribute assigned to certain word senses of a cluster.

• Coherent Sense Attribute: is a word sense that provides the zero point of reference to a dynamic situation. The zero point sets the bias to a set of potential conditions in the world (e.g., slide 1.7).

The system basically follows its rules and priors to then prescribe the attribute to the kind of content that fits the criteria. Depending on prior relationships, the analysis asks, how is a particular word a coherent core to particular conditions or how is a particular word a condition of a coherent core? A word sense being either coherent or conditional will depend on the general situational relationships dynamically implicated in the system. As we will show later, this process involves scripts that sequence Q-units and allows any word to participate as a coherent or conditional factor.

Self & Other: Humans interface with machines through Q-units. Q-units are optimized by human operators who tweak the coherent-conditional states. Q analysis is propelled by a very important categorical intuition – it is the human intuition of being self aware in a social world.

 “I need an answer to my question”.

In the Q system, the social-self and social-world are categorically divided. The category of the self-coherent is in various dynamical relationships with categories of the other-coherent. Theoretically, the dynamical relationships between them are broken down into different conditional terms that are used for predicting the interactions between them. Interactions with others and the world can be repurposed offline. In other words, the motivations behind those social or environmental conditions can be used to generate relational predictions that are wholly imaginary.

“Gateway to another world.”

Since interactions can be repurposed, a coherent sense is not necessarily about truth relations with the world. Off line, the system can generate variations on procedural scripts repurposed for dynamical objectives. As stated, the coherent sense is an attribute prescribed by the system. Interacting with others optimizes the system’s situational objectives.

• Theoretically, a conservation of order is provided by the coherent factor. In other words, a conflict between coherent and conditional factors will generate new Q-units.  In a response to new input, the goal is to produce like minded objectives in a reciprocal relationship with others to organize the conditions in the objective field as probable outcomes in the world.
  

Contextual Units:

When there is some knowledge necessary the solution here is to find the contextual unit with the coherent sense best suited to deal with the condition. It’s like being in the right state of mind to deal with a problem. Marvin Minsky called it different ways of thinking. This can be associated with his panalogies, and panalogies can be associated with metaphoric kinds of relationships between local realms that are connected by global roles. Next, we’ll imagine how these realms can form in a Q system.

Word sensibility is about contextual traces and contextual traces are about word senses, not just mapping between them but being able to generate them. Word sense will change over time providing a new word sense. To describe generating word-sensibility, we use the analogy of a cell splitting; a word sense begins as one categorical cluster of words (e.g., synsets), then the words begin to separate. Think of a Q unit as a circle, within the circle coherent words are moved toward the outside while conditional words are moved to the inside. A new circle forms inside the circle, from here it can split and form a new circle. Conditional terms of the parent become a new child of coherent terms, the new circle then splits again and on it goes. Consider the word bird between two distinct coherent-conditional states.

Above, conditional bird types becomes a coherent version of bird types, it’s a new coherent role different from prototypes. Bird types begins the process of separation. A new individuated state of bird can take form as a unit if and only if viable potential conditions can establish.

• The coherent sense attributed to the term bird is different from the conditional sense attributed to the term. A coherent core is a constraint for a range of conditions. Any contextual trace is either coherent or conditional. Every word is virtually a contextual trace where understanding the dynamical context of it depends on this relationship.

The illustration above is about more than we covered, but it may help to consider how there can be variations on the splitting cell. Above refers to different dynamics of bird. Here, a different kind of separation is illustrated. The separation is between mode and state clusters as apposed both clusters being states. On the left is subject/state, on the right is the predicate/mode. It is two complimentary ways of being coherent sense and two complimentary ways of becoming conditional sense. The left side represents a being or subject/state, the right side represents an action or predicate/mode. This illustration is another example of a complete Q unit. Without getting in to a lot of detail, the mode represents how the action or measure between a coherent state and conditional state is coupled. We will address mode and sates more in the Q model overview.

It can be a little confusing because Q categories are not like normal taxonomies. One might want to see the genus term bird as coherent and some species(x) as conditional. Although this potential can be seen in the child example the parent uses different roles, specifically, prototypicality; the coherence is based on some particular prototype to predict birds in the world. To know something is often just a matter of having a good example from your surroundings. The potential world provides bird types and this is represented as conditions found in a particular cluster called the objective field. Any deviations from the coherent sense is there, we will revisit this later. How the conditions are handled depends on modes (actions). The idea is to draw conditional senses into a coherency, almost like currency. There are several ways to address a coherent sense, here are a few:

• coherent-bias: referencing from a Q-unit.
  
• naive-standpoint: referencing/referring to Q-units.
• zero-point: pertaining to a reference frame.
• resonance:  responding to something.
  

Weighted Inferences & Parallel Analogies:

Below is an example of prototypicality. A coherent bias robin is providing the actual sense of the word, bird. The conditional senses are potential bird types. Any major deviation from the coherent sense robin is potential for conflict and causing it to split.

The Q children stay somewhat connected to the Q parent by how they align – each Q unit tends to justify with its parent – they are in a sense like minded. Inferences between them are not always apparent at first. Inferences will begin as non-logical connections but can produce useful metaphoric opportunities for logical inferences later. They are less like word sense inferences and more like analogous relationships. They help word senses scale tracts of contextuality by providing metaphoric kinds of relationships. Below are Q-units or realms connected by roles providing parallel analogies. Each dimension acquires a particular role for a topic.

Q textual analysis aims to span from single word-topic delineations to theme-topic delineations captured from portions of text. Content left out of the analysis are potential conditional factors for those environs that fulfilled criteria. Theoretically, Q-units are not rational, the process begins as almost random clustering but becomes essential to creative thinking as well as normalized ways of thinking. Ways of thinking are arranged in a simple matrix. Each dimension of the matrix pulls together its own cluster as we will see later. Q-units can subsume or be subsumed by other Q-units. Q-units pull together network clusters to be criticized in objective fields.

Self Identity:

Q-units form granularities including, hierarchies, domains, realms and roles. It is important to note that a word-sensibility system renders no one true hierarchical structure over the whole system, hierarchical structures compete for global status but a sense of coherent self is formed essentially from bias; a sense of self is always a local system and never a global one. Every Q-unit is virtually a self Identification opportunity.

The Dynamical Context:

On one hand, the process keeps a Q unit united with its dimensions. On the other hand, the process divides a Q unit to form a new Q unit. The process can be described as interactions between contextual units forming nested dynamical contexts. In this description, contextual units draw upon contextual hierarchical structures and then gives back to it, thus, participating in an ecology of dynamical systems. A conflict with the principle of the conservation of coherence (order as a position, for instance, robin to remaining the coherent core of bird) provides for the emergence of systems. The process fits a fractal description where a domain is presented as a Q-unit as is a realm as is a role in a recurring pattern.

The emergence of systems is a self identification opportunity that applies to the dynamic development of a situation and where the self is positioned in that development. The dynamical contexts orients the self towards potential conditions for easy predictions and/or coping solutions.

There are many  kinds of human expressions where a sensibility model might apply, such as, music, literature, humor or religion. All of these human sensibilities share the common root of social cognitive dynamical systems. In the simulation hypothesis, the mind is said to re-purpose perceptual systems to find meaning in language. So, in some correlation, the theoretical mechanism of our model will likewise assist in presenting meaning by re-purposing basic forms of perception to ground our sensibilities that also constrains a variety of other expressions.

Sensibility & Music: To think of music in relation to the sensibility model we can consider how embodied simulations essentially source experiential oscillations, such as, urge and resolve cycles. These cycles refer to organismic tendencies or existential systematicity, such as, seeking food for sustenance or mates for procreation. We suggest that these cycles help structure our dynamical interactions with the world forming procedural scripts that can be re-rendered. Consider how musical composers employ anticipation and resolve techniques in their compositions to keep listeners engaged in a musical development. In our view, and without going into the details involving valence and objective musical features, this relates to an involuntary response toward a coherent bias and implicates a resonance with a dynamic development. Here, there is an opportunity to develop an internal identity with an external development. In this way, music is a proto-narrative that begins a deictic sense of the self to establish a coherent bias. The utility of sensibility is to render a coherent bias. Music extends a proto-narrative out as pure potential for dynamical contextuality to which one and others are prompted to form coherent bias.

Sensibility & Humor: There was once a popular YouTube video. It starred a cat that could clearly see people and other animals passing easily in and out of a screenless screen door. The cat just sat there, amusingly unimpressed, until someone swings open the ineffective screen door frame “the barrier” and only then does the cat trot through. No doubt, this is basic funny stuff. The humor here, in our view, is related to the spatial bias aligned over the cat’s passage bias. Obviously conditioned for certain potentials, such as, human assistance, and not syncing to the bias cues in the actions of others. The cat is unable to find autonomy. Human autonomy relies on multi-nested levels of coherent biases, the more coherent biases the more ways to reflect, sync and then act. Since the circumstance is coherent to humans and not to the cat a human might enjoy an empathetic flux from the potential of the condition to the clear actual coherency that the cat has no bias for, on cue, humans find humor. Humor is audible with laughter and visual with smile. It seems that these behaviors signal when one feels a sense of coherency with another. Humor is also a way to intimidate by posturing superior coherency causing another a stressful situation as if being reduced to a mere condition of another’s bias. On the other hand, it is also a way to defuse the stress that comes from attaining social coherency. Of course, it is more stress relieving for humans than cats to amass spatial and social circumstantial understandings, like doors and jokes.

• Humans seek to take account of each other by monitoring the coherent and conditional oscillations autogenously in sync to behaviors innately merited kindred.

There are internalized social dynamics between the intra-personal coherent biases that swing from nurturing to competing. The coherent bias of a Q-unit is virtually a stand-point that will compete for general positions in a system. Coherent-conditional roles extends out from self to society and loops back to self in a reciprocal causation.

All positions global or otherwise are always a standpoint to particular conditions. A standpoint has an active state that means more experience necessary and has a passive state that means no more experience necessary. A system oscillates between these two states essentially closing the loop on a particular problem. Above, the coherent agent Marie is a network of oscillating dimensions, the conditional agent Pierre, pays attention and oscillates with her. Marie’s oscillations are extended out to Pierre to address her conditions, not Pierre’s. As it is, Marie is the agent and Pierre is the patient.

Above, the oscillations forms an intimating script. The environment drives the subjective/coherent sense, remembering guides the objective/conditional sense.

We now turn our attention to scripts, layers, polynyms and the idea of Meta-Dimensional Roles.

Q layers: The system runs scripts one at a time or different scripts simultaneously on different layers. Dividing the scripts into layers allows each layer to focus on a particular job. Polynyms represent the layers. Layering is a strategy, it is essentially the system analyzing and dividing up the procedures so it’s faster and easier to process.

A polynym can be a quick strategy or a general architecture for an entire system, consider the illustration above. A polynym can be reconfigured, however, the more general a polynym is in the system the harder to change. In polynym layers, slower general scripts constrain faster specific scripts.

Every polynym dimension represents a quadranym, a quadranym is a single frame of a script, so a polynym dimension is a single script. For instance, notice in the illustration above, the motivate system layer 2 runs a script. Q-units and scripts contain a class of content called, Meta-dimensional roles. Urge ⊇ Resolve are meta-dimensional roles.

Meta-Dimensional roles are general categorical units that aim to ground and guide the use of normal content in a cycle of reciprocity. To be clear, we are not claiming that Meta-dimensional roles actually exist, they are used to represent human experience and behavior. Any word can eventually become a Meta-Dimensional role in the Q system.

Next, a closer look at the basic Q components:

Meta-Dimensional roles

References

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