Hardware and software of the brain

The methods to define a concrete object (to create an instance) may vary. You may mention a class in concrete circumstances. 'A cup stands on the table.' Since then, this class turns into the object and you can use this word with the new meaning. Additional details may be added in separate sentences. All of them will be linked to the same object. After that, it is possible to use this object in some action.

Otherwise you may use the relative clause. 'Take the cup that stands on the table.' Here, all is done inside one sentence. There is also a difference in general use. Programming languages use classes mostly to define their methods and properties and to create object instances from them. The program will use that objects afterwards. Human language, in contrast, manipulates classes and concrete objects in equal degree.

Indirect meaning

All these elements represent the direct meaning of a text. There is also an indirect meaning in addition. It is produced by reasoning. For example: "The price of item1 was $10 last month. The price of item1 is $8 now." The conclusion from this short text will be: "The price dropped." Indirect meaning is always pragmatical that is dependent on the situation. For one person one feature of the sentences is important. For the second – another one. Their conclusions may be different. Context-free languages restrict their semantic scope to direct meaning. This is a relatively simple task routinely solved by standard programming languages. What do humans use in addition?

Semantic transformations

Associative memory of neural nets not only stores data but also provides various processing based on similarity immediately on the hardware level. This is widely used during language understanding.

Anaphora

Pronouns are analogous to variables in programming, but their usage is peculiar. In strict languages, you must declare the type of a variable, then assign a value to it; only then you may use this variable in some expression. In natural language, you just use 'it' which refers to some previously mentioned noun. 'A cup stands on the table. It is large and bright.' The reader often guesses which one you keep in mind. Human language has an even more vague but simultaneously more embracing feature. 'it' or 'this' may refer to the whole paragraph describing some phenomenon of any nature possible. It may be a material object, an action, or even a relation.

Metaphor

This is similar to the theory of analogy which is well developed in physics. The principle is that if we have one phenomenon that is perfectly studied and another one which is barely known but has some analogy with the first, then we can transfer the source knowledge to the target. For example, Hinduism tells that our world is not the first, but before it was created, Shiva destroyed the previous one using a swift dance.

Fig. 15. Shiva as Lord of Dance.

The study of metaphors discovers how we process information. The human brain is very efficient for the comparison by similarity. Neural nets do it immediately in associative memory on the hardware level. Accordingly, we have various types of metaphor.

Allegory

This is an extended type such as fables. They usually employ animals or other non-human creatures to illustrate some moral principle. The story is full of details and stimulates profound thinking.

Hyperbole

Underlines some features by means of exaggeration. A typical example of hyperbole is "million reasons".

Parable

Parables are sample stories for educational purposes. They were actively used by Jesus Christ. In contrast to a fable, it excludes animals or inanimate objects representing speaking beings.

Antithesis

Natural language works with fuzzy objects. In such conditions, it is useful to underline not only some features, but also their negations. In the following sample, antithesis is used to underline a paradox: "The better – the worse; the worse – the better."

Metonymy

In this case, a concept is designated by the name which calls a close association. As an example, a crown is a well decorated headwear, but the word is also used for a royal house or power.

Connotation

As you know, songs convey 2 components – text and music. They correspond to information and emotions. Both are well represented in common speech. In pure texts the second is limited but also present as well. For this purpose we use various synonyms. For such words the meaning is similar but not exactly identical. The difference of the second order may convey our attitude to what we write.

Implicature

When we communicate some useful information, formulating everything explicitly would be boring, especially in dynamic circumstances. By this reason, we usually say essentials taking the rest for granted. For example, when one explains the recipe of a soup, he may enumerate the necessary vegetables, but don't mention salt.

Theory of language

At present, there are many different theories for parts of language such as syntax and language as a whole. Consensus is even not visible, but most of them are, in fact, variants of the same or different solutions of some particular question such as what is the main word of the sentence. Hence, we can formulate a generalized theory taking the best ideas from different approaches or choosing the most practical method for particular problems.

When you create some science from scratch, finding solutions of key problems is the second step. The first – formulating these problems and defining appropriate terms for them.

Natural language as a whole is a communication system for the transmission of 2D cortical images over an 1D sequential channel. Basically, 1 sentence = 1 image. The next sentence either adds details to the existing image or creates a new one. The main problem is how to group words inside the sentence. For this purpose, civilization adds grammar. The Part Of Speech (POS) is an entirely artificial concept. In fact, syntax and punctuation introduce an intermediate level of processing. POS + syntax rules define grouping.

The standard pipeline of language processing is

POS -> Syntax -> Semantics -> Pragmatics

The question is how different steps (levels) interact with each other. A popular principle is that syntax should be self-sufficient, that is independent of adjacent levels from both sides. Word grouping should proceed without words themselves. Only their POS is needed. Also parsing of the sentence should be completed before proceeding to semantic analysis. It is on this next stage that words fill the parse frame. The final meaning is created on the last, pragmatical level taking into account the other sentences of the text.

Unfortunately, this is only a good wish which is possible only for very strict artificial languages. Even for moderately restricted natural language it is impossible. Most words may be several different POS. Accordingly, for each sentence several parse structures are possible. Humans choose one by meaning. For this purpose, the system of analysis should have full backtracking through the whole pipeline.

Another problem is workability of syntax itself. If we take standard English, it has wide variety of phrases on the sub-sentence level. Even filled with real words, such phrases may create an ambiguous construct. The probability will be only higher if we consider POS only. The longer a sentence, the more phrases it contains, the less reliable it is.

Finally, alongside generalized syntax, humans widely use various expressions based on concrete words. Such expressions may form the whole sentence or only a phrase within it.

Human language is like a programming language without automatic error checking. It is up to the users to reduce ambiguity. Human language is very redundant so there are plenty of abilities. Don't attach too many POS to a single word. Say, English syntax allows a noun as an attribute to another noun. Hence no need to declare it as an adjective in the dictionary. Don't use long sentences with several clauses. Break them down to simple sentences. If you see that some construct is ambiguous, replace it. Usually there are several ways to say the same thing.

Computing

A text supplies us with some knowledge that we use later for practical purposes. Which specifically? The term of intelligence may be defined as the ability of problem solving. That's why knowledge accumulation is needed. Let's analyze in details how it happens.

Syntax

Separate words group into phrases, clauses, and sentences. Then into paragraphs, chapters, books, and whole libraries. The structure over the sentence is less standardized. An encyclopedia is like a library, only the latter may contain several books by different authors on the same topic. In the encyclopedia they are concentrated into a single article.

Syntax is a completely artificial formal system. Ideally, it should be detached from both lexicon and semantics. Word grouping should depend only on the part of speech. In real languages, there are lots of exclusions from this principle, but even without them formal grammars are problematic. Let's look into details of these problems.

1. How to represent the structure of the sentence on the very top level? The popular answer is

sentence(subject phrase, predicate phrase)

Both arguments are equal here. Alternatively, one of them is considered the main. If this is the predicate, human sentences become compatible with formal logic

predicate(subject phrase, predicate phrase)

Here the subject will be just one argument of the predicate (in logical sense) alongside the direct object and the other members of the sentence. Also the semantic load of this representation is clear. In this case, each sentence represents some action and the whole text answers the question: "What happens around?"

2. During word grouping, the process passes a hierarchy. Different textbooks present it differently. Some levels may be absent. At the first step, various phrases of the lexical level are recognized. These are: noun phrase, verb phrase, adjective phrase, adverb phrase, prepositional phrase.

At the second, they create phrases of the sentence level: subject phrase, predicate phrase. Secondary members of the sentence, such as the direct object, are usually not single words but whole lexical phrases. Note that the same noun phrase may become either a direct object or a subject.

A clause is like a simple sentence, only as a part of a complex or compound sentence.

Semantics

When syntax analysis is completed, semantics is available by taking into account not only parts of speech, but the words themselves. Meanwhile some part of meaning may be restored already from the syntax structure. Usually a noun corresponds to some object, a verb – to an action. Of course, there are different variants too, but all of them may be explicitly enumerated. Then, we will have a general description of semantics in possible details. If such a description is implemented programmatically, it is enough to supply some dictionary and the program will correctly understand any text composed of these words.

Some addition to the previous Formal semantics

While conjunctions represent relations between clauses, that is actions, prepositions – between objects represented by noun phrases. Generally, there are 2 of them. The second immediately follows the preposition, but what is the first? If the prepositional phrase stands after the subject, it is linked to this subject. If it is a part of the predicate phrase, there are several variants. It may be a prepositional object. 'We spoke about computers.' An adverbial modifier. 'He lives in this town.' Also, it may be an attribute to some noun in the predicate phrase. 'He moved to the table in the corner.' That is the table which stands in the corner.

In the first 2 cases, the first element of the relation expressed by the preposition is the subject. In the third, the whole construct is ellipsis of some relative clause as explained for this particular example.

Long sentences using complicated structures of modern English syntax may usually be dissected into a set of short simple sentences. After that transformation, it becomes clear how humans process such constructs. For the last example, if there are 2 or more tables in the room, we need clarification. Which one? The sentence may be rewritten. 'A table stands in the corner. He moved to this table.'

How do we use this knowledge? There are 2 typical applications: question answering and problem solving. In the first case, the system will retrieve existing data or derive the answer using its inference engine.

In the second, knowledge is used to find an algorithm of solution. Suppose a service robot has got the order: "Bring a bottle of Cola to me." The machine needs to know where it is. The knowledge base contains records which tell that Cola is in the refrigerator which stands in the kitchen. This is enough to calculate the destination for the navigation system.

Words on the sub-sentence level group according to syntax, but also have semantic roles. The same principle works on higher levels. When we read a text sentence by sentence, they produce some ideas in our mind. They may be remembered for later use or exist temporarily just for the process of reading. These ideas may belong to a few different semantic categories.

Facts

If the sentence has a predicate, it denotes some action. 'The corporation A purchased the startup B.' Although, actions may be static. In this case, they denote a state of some object. 'A pear hangs on the tree.' Such sentences immediately add details to the existing picture of the world. Before we remember them, they usually pass the filter of validity. Some facts may be just impossible so should be rejected. Some – negligible. Don't pay attention.

Explanation

If the fact is improbable but still valid, it needs explanation which opens the filter. Oftentimes such facts become especially valuable. Explanation usually reveals the reasons of why it became possible and, as a rule, is intended for temporary use. Although, in thorough reading the person may analyze and remember something from the explanation so as to use it later in similar cases.

Proof

This is a more formalized variant of explanation. Usually it employs logical inference and derives the result from known facts and rules.

Conclusion

Human logics uses rules. They have various facts as conditions in their body. These facts may be either present explicitly in the knowledge base or derived from other rules. Sometimes the needed logical inference may be lengthy so a text may formulate the conclusion for remembering. After that, it becomes a new fact which does not require proof.

Detailing

The first sentence of a paragraph or the heading of a chapter usually creates a new image in perception. The next sentences add details to this image. The next paragraph of the chapter adds the whole of a new image inside the larger image.

Nucleus Language

The nucleus language is a minimally sufficient set of elements for general-purpose communication.

Being explicitly formulated, it has wide variety of applications: human-computer communication, normalization of human texts, language teaching …

A real language consists of this nucleus + general-purpose extension (lexical and syntax synonymy, rare processing functions, etc.) + professional (special) languages.

The elements included are quite different. The most known component is lexicon – some minimal dictionary of the most used words. At the syntax level, these elements are represented by non-terminal nodes of the parse tree which reside between 'Sentence' and 'Word'. Syntax is about word grouping, but this process goes through a few intermediate levels. For English, the hierarchy is: Word -> Phrase -> Clause -> Sentence. The categories may be related to separate words or to sentences. Accordingly, grammar may use parts of speech (noun, verb …) or members of the sentence (subject, predicate …). These categories are not synonyms. Just substantially overlap, but there are differences too. A noun phrase may serve as a subject phrase or direct object. The prepositional phrase requires a separate discussion.

Syntax is not completely detached from semantics. Indeed, parsing using just parts of speech, not words themselves, is preferable, but even parts of speech still have some generalized semantic load. Both prepositions and conjunctions represent some relations. Prepositions – between nouns (or equivalent words). Conjunctions link homogeneous members of the sentence or clauses in compound and complex sentences. Prepositions represent physical while conjunctions – logical relations. Formal logic turned conjunctions of human language into logical functions.

Accordingly, using 'prepositional phrases' is not semantically correct. Each preposition usually requires 2 nouns like in 'a cat with the long tail' -> with(cat, long tail). This draws far-reaching consequences for the whole structure of the sentence. The predicate phrase can contain a prepositional object. 'He took the bread with butter.' -> with(bread, butter) What if there is no direct object? 'He came with his friend.' -> with(he, his friend) In this case, the preposition links its object with the subject. This is not a well formed solution because objects are parts of the predicate phrase and the link goes over the predicate. We can resolve this issue if we abandon the traditional structure sentence(subject phrase, predicate phrase) and replace it with more logicist

predicate(subject, indirect object, direct object, prepositional object, adverbials)

Semantics of such a format is clear. Each sentence represents some action. If nothing changes like in: 'The box stands on the table.', this is just a static action. In any case, the picture is a function of time. The subject is different from objects only by attracting more attention. It is even not required that it should be the actor. 'The apple was taken by his friend.' In passive voice, the subject is the word with the semantic role of the direct object. This is because attention is directed at this object.

Such generalized semantics independent of particular words may be implemented directly in the program while semantical properties of different words require some dictionary. All in all, the following semantically significant elements may be distinguished in the simple sentence. 1. The predicate (verb). 2. Various noun phrases. 3. Adverbs which are not a part of some noun phrase where they modify an adjective. Such adverbs modify the verb. 4. Prepositions and conjunctions. The former represent relations between noun phrases. The latter – between clauses. They also may link homogeneous members of the sentence. Conjunctions work like logical functions in a list.

predicate(subject phrases, prepositional phrases, adverbs) conjunction predicate() …

Besides these basic elements, there are many derivatives. 1. The gerund is a noun-type word created from a verb. 2. The verb also can produce forms which function as an adjective or an adverb. These are participles.

The first noun phrase is the subject. This category should be retained if we want to answer standard human questions. The indirect object is redundant. It may be replaced by the corresponding prepositional object. 'I gave him an apple.' -> 'I gave an apple to him.' The second variant is more reliable for parsing. Only it should be present in the nucleus language. Adverbials may be represented either by a prepositional phrase or by an adverb. The first is often difficult to distinguish from the prepositional object. 'I came with my friend.' 'With' in the prepositional object. 'I lifted it with my hands.' The same in the adverbial of manner. This can be cleared only from low-level semantics. That is, regarding particular words involved. In some cases, it is impossible to distinguish the roles at all. Both are applicable so leaving prepositional phrase in the representation is justified. Then, its semantics should be computed when it is used in inference or question answering. Finally, conjunctions represent relations between simple sentences as clauses.

You see, there are quite a few basic elements. One difference of natural language from programming languages is its universality. It is used both for abstract computations and machine-level programming. Probably these elements represent some very basic operations performed by neural nets. For example, a noun phrase may stand for an image which is a part of a larger construct while prepositions and conjunctions define how these constructs are built of such images. Details of the procedure are defined by the verb in question. Say, if it is intransitive, there won't be any direct object at all. If the verb is transitive and the object is present, the details of object's handling are defined by this verb.

The nucleus language should contain only the most necessary items. On the other hand, human sentences may be very extended. Obviously, they are being broken down to more primitive ones during understanding.

Abstract semantics represents various functions which our live neural nets perform when we process textual data. Being explicitly listed and properly arranged, they may serve as ready terms of reference for software development.

Semantics is hierarchical. There is meaning associated with particular words and there are generalized categories. Let's list them explicitly.

Natural language actively uses attributes. Normally, adjectives modify nouns and adverbs – verbs. However modern languages add many extensions. Adverbs can also modify adjectives. A noun may be an attribute for another noun. Normally, this is expressed by a prepositional phrase after it. 'the leg of a chair', 'a cat with the tail'. In addition, English can put it in front of the noun. 'the chair's leg' or even 'the chair leg'. The exact semantical relation between the attribute and its object is defined by the preposition used. It is necessary to note that the last sample may be modelled also using the dictionary. The noun before another noun may be declared as an adjective. In this case the trouble just moves from syntax to the lexical level. Best of all – to avoid such constructs because they make parsing inefficient.

Gerund is a noun-type word derived from a verb. Interesting that it retains the structure of a verb phrase which begins functioning as a noun phrase. The verb can also produce forms which operate like adjectives or adverbs. These are participles. What is the meaning of this variety? If the verb is represented in neural nets as a movie, then gerund is a snapshot from this movie. The action as an attribute of a noun (a running man) means that this noun participates in this action. The inversion is similar to the passive voice and serves the same goal – to switch attention from one member of the sentence to another. In this case – from the verb to the noun. The action as an adverb, that is an attribute of another action, ('he did it laughing') means that the first action is a part of the second.

Passive voice may be easily explained if we take the predicate as the main member of the sentence and the subject as just one object which gets maximal attention. Passive voice switches this attention. It becomes indispensable when the subject is absent in the active variant. 'The precedent was created.'

In complex sentences, a subordinate clause takes place of one member of the sentence and accordingly plays its role. In compound sentences, coordinated clauses are linked with a conjunction which works as a logical function. This makes it possible to compare natural language with mathematics. You see that formal logics added parentheses which group members of the list and made semantics of functions (and, or, not) absolutely definite (which is not the case in human communication). On the other hand, the list of natural conjunctions is not limited to these 3 ones. Accordingly, the rest of them (such as 'but') may have similar, but slightly different semantics.