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Now that we’ve familiarized ourselves with the primary entities of the human knowledge base, let’s see how these entities can be represented in language.

In the realm of linguistics, we’ll take the top-down approach as well, as we apply the structure of our neural network onto the creation of lingual representations.

Basic Nodes – C1 & C2

The most basic structure on a neural network is the node. In our case, the C1 & C2 primary nodes. These nodes can use labels, or names to represent them.

These nodes are represented as the individual words of the language.

  • Jack, tree, table, person, jogging, movement, cutting, chopping, squeeze, and so on.

or word combinations

  • Jack Dorsey, apple tree, rocket launching

Complex Nodes – C3 & C4

The more complex C3 & C4 nodes may also be labeled and named, but there are usually agreed-upon patterns of word combinations that could represent them.

These naming conventions may define the structure and describe the commonalities of the group, the order of the hierarchy, and/or the required qualifications.

  • C3 Picker: “The best author”
  • C3 Finder: “The biggest spoon in the drawer”
  • C4 Group: “The (whole) family”
  • C4 Fetcher: “The spoons in the drawer”

The Basic Primary Connections

Now that we have actions, things, groups, and hierarchies, we need to put them together. This is where the next entity type comes in – the connection. But, by connection I don’t mean the usual straight forward A to B kind.

Mental connections are more like junctions, as they usually connect between 3 different entities (S-V-O), and sometimes even 4.

Simple Connections between C1 & C2 nodes

  • Events: “He was writing. He wrote a book
  • Position: “It is on/in/under the couch
  • Metadata: “This action/plan/person is difficult

Simple Connections with C3 & C4 nodes

These sentences increase in complexity when combined with more complex nodes.

  • The best author in the world wrote a book
  • The knives in the drawer are sharp

Conjunctions – Members of the Same Node

These connections, just like any other entities, can be collected together by a C3 or C4 nodes, represented as conjunctions.

  • Addition: “Eat healthily, and exercise regularly.”
    With emphasis/priority: “This is fine, but that is not.”
  • Options: “Go out, or stay home.”

Compound Sentences – Connections Between Connections

The formal basic graph structure of connections between nodes is simple. The mind, however, is quite a bit more complex. In the mind’s knowledge base, connections are not only possible between nodes, but also between other connections.

Such connections would be represented by language as compound sentences.

  • Comparison: I ride a bike better than you ride a bike.
  • Associations: I was walking with my dog.
  • Affiliation: “Death is part of life
  • Sequence: “First listen, then ask questions
  • Requirement: “In order to run, you must first learn to walk

Additional Connection Detail

Another great benefit of having connections emerge out of other connections is the ability to add additional custom data to connections, just as we do with nodes. These are used to convey additional information about the specific nature of the connection, such as time, place, context, opinion, intensity, etc’.

  • Certainty: “He was (definitely) running
  • Speed: “He was running (very fast)”
  • Time: “He was running (last night)”

Since these additions are ‘owned’ by the connection, and refer to the clause as a whole, their position in the sentence is merely a convention. Yoda-speak (e.g. very fast he was running), even though breaking conventions, is still completely comprehensible since all we’re really looking for in a sentence is the existence of nodes, the connection between them, and the additional connection details.

* When it comes to subject and object though, in English, placing does matter and the subject must come first. In other languages though, there might be additional clues and modifications that identify the subject and the object, making their position optional as well.