Hierarchy of Language.
Abstract. Geller’s Differential Linguistics and his patents are studied, they are shown as the
development of Wittgenstein’s Tractatus Logico-Philosophicus and Moore’s Truth and Falsity.
The only hierarchy of language – text’s context and surrounding it multiplicity of subtexts – is
thoroughly examined; nature of text’s predicative phrases, clauses, sentences and paragraphs is
clarified.
The novel approach toward Knowledge is proposed: Knowledge is Nothing, singularity; there is
the Nothingness of silence, none-predicative definition and text.
The practical proofs of Differential Linguistics as the first ever verified Humanitarian theory are
demonstrated.
Keywords:
Knowledge;
Wittgenstein;
Moore;
Russell;
Differential Linguistics;
Hierarchy;
Clause;
Sentence;
Paragraph;
Weight;
Emotion;
Practical proofs;
Nothing;
Patents
***
Geller suggests that only one hierarchy in language exists: text’s context and surrounding it
multiplicity of subtexts; where they are composed by sets of paragraphs, sentences, clauses and
predicative definitions (US Patent 8516013).
That hierarchy was initially established by Ludwig Wittgenstein in his famous Tractatus LogicoPhilosophicus, developed, detailed and finalized (as Differential Linguistics and patents) by Ilya
Geller and practically implemented by Google (Sergey Brin and Larry Page), IBM, Microsoft,
LexisNexis, all other Internet and some database companies.
I.
1
1.
Mathematics.
Sets Theory1 is the theory that Geller use; where the basic units of the sets are words
(Geller 2005):

none-predicative definitions2 are the words;
Set Theory is the branch of mathematical logic that studies sets, which are collections of objects.
Wittgenstein said on the words, at 3.26: ‘The name cannot be analysed further by any definition. It is a
primitive sign’.
2





predicative definitions are always pluralities of the none-predicative definitions;
clauses may both be pluralities and singularities of the predicative definitions;
sentences may both be pluralities and singularities of the clauses;
paragraphs may both be pluralities and singularities of the sentences;
texts are always pluralities of the paragraphs.
The sets always intersect3, the basic units do not.
2. The predicative phrases are vectors of meaning. The intersections of sentencesparagraphs determine a) the vectors directions (the texts’ sense) and b) emotional
significances of the vectors, as weights (US Patent 8504580).
Wittgenstein came to the same idea, at 3.261: ‘…the definitions show the way.’
I am unaware of any author who wrote on sets of weighted vectors filtered and aimed by
intersections of clauses-sentences-paragraphs as sets (Clark 2014).
II.
Axiom.
Geller’s Axiom: words exist (Geller 2005). I don’t think the Axiom can be challenged.
III.
Definitions.
Now, I explain what Ludwig Wittgenstein and Geller mean by the abovementioned Linguistical
categories:
1. Predictive definition: Poincare.
‘A predicative phrase is a predicative definition preferably characterized by combinations of
nouns and other parts of speech, such as a verb and an adjective and an article (e.g., the-grey-cityis) (US Patent 8447789).’ Geller decided that a predicative phrase4 may have undefined number
of words as parts-of-speech, and it should answer at least these three questions: ‘What?’, ‘What is
going on with ‘what’?’ and ‘How does it look like?’5 (Geller 2003, Geller 2005 and US Patent
8504580).
Geller pedantically followed Poincare’s instructions, filing his patents and writing his articles:
‘Logical inferences alone are epistemically inadequate to express the essential structure of a
genuine mathematical reasoning in view of its understandability… As a consequence of the
logical antinomies, one should avoid any impredicative concept formation (Poincare 1920).’
All authors in Philosophy (of Language) and (Computational) Linguistics sooner or later discuss
(contextual) phrases and/ or vectors of sense:
3
In mathematics, the intersection A ∩ B of two sets A and B is the set that contains all elements of A that
also belong to B (or equivalently, all elements of B that also belong to A), but no other elements
4
Wittgenstein said on predictive phrase, at 3.261 and 3.262 and Geller thinks the same: ‘Every defined sign
signifies via those signs by which it is defined, and the definitions show the way… What does not get
expressed in the sign is shown by its application. What the signs conceal, their application declares.’
5
'...on another dataset of Usenet newsgroup articles he instead found also 3-grams to have some utility,
whereas the negative contribution of larger n-grams was confirmed.' (Caropreso 2000)




Phrases may have undefined number of words;
Phrases are obtained from sentences;
Unclear the role of clauses into the obtaining of phrases;
Phrases’ words belong to unknown number of parts-of-speech, usually one, two or three,
the phrases may not be predicative phrases (have no verbs);
 Not a method provided how to identify objectively, without any human intervention, the
parts-of-speech of words;
 None of the authors, Wittgenstein included, uses Sets Theory and Differential Analyses,
finding how sets of phrases convey text meaning;
 None of the authors linked weights of vectors to their emotional strength (Clark 2012,
Clark 2014, Beltagy 2014, Boleda 2013, Guevara 2010 and Wittgenstein 1994).
Geller operates with predicative definitions as with featureless numbers, he does not see external
features.
2. Clause.
Geller said: ‘AI Clone treats each clause of a sentence as an individual sentence – the clauses are
preferably determined based upon figures of speech and punctuation marks. For example, a
semicolon or comma followed by a “but” may indicate a division between clauses if they separate
a subject and predicate pair (US Patent 8504580).’
Wittgenstein said (at 3.31) that each part of a proposition which characterizes its sense is called an
expression. However, Wittgenstein was unclear and did not explain what he meant, as Geller did,
filing his patents. Did Wittgenstein mean phrases? Grammatical divisions – clauses? His
‘complex’ is too vague the definition (at 2.0201). The fact that Geller was granted the US Patent
8504580 is the undoubted evidence that Geller has the priority and there is no prior art.
3. Sentence.
A sentence is a subdivision of a paragraph, separated by certain grammatical signs.
All authors on Philosophy and Linguistics, since the time of Ancient Greece, without a single
exception, studied sentences as the major grammatical division of language; but none of them
ever analyzed their role as subdivisions of paragraphs, into targeting and emotional weighting of
the vectors.
1. Paragraph.
In US Patent 8516013 Geller equated paragraphs to passages: ‘A passage in this context can be
any suitable amount of text that can be treated as a paragraph, and may actually be a paragraph…
A paragraph can be a subdivision of a written composition that comprises one or more sentences,
deals with one or more points/ideas, or gives the words of one speaker…’
I don’t know any attempt of any author to study the passages-and/or-paragraphs as sets of pointed
and weighted vectors, their role in the pointing and weighting.
4. Subtext.
Geller: ‘The term subtext is used to include information other than or in addition to actual words
of text. Subtext refers to information that is not explicit in a text but is or may become something
that may be gleaned from the text and/or from related text (US Patent 8504580).’
Here, Geller refers to the idea in Tractatus, at 3.263: ‘The meanings of primitive signs can be
explained by elucidations. Elucidations are propositions which contain the primitive signs. They
can, therefore, only be understood when the meanings of these signs are already known.’
Geller, in his US Patent 8447789, proposed to use the most appropriate definitions from
dictionary as subtexts; these definitions are always paragraphs6: no prior art.
5. Context.
Geller: ‘Context provides the textual description of present circumstances for subjects/objects;
while subtext provides textual description of related to context descriptions of circumstances for
the same subjects/objects (US Patent 8504580).’
Wittgenstein left a hint, at 3.3: ‘Only the proposition has sense; only in the context of a
proposition has a name meaning.’ All authors in (Computational) Linguistics deal with context,
all mention it: none see they have no sense without subtexts, none analyze its role into aiming and
weighting of vectors.
6. Intersection.
The intersections between predicative phrases, clauses, sentences and paragraphs are formed by
synonymous predicative definitions (US Paten 8516013).
The fact that Geller was granted the US Patent is the proof he is the first and no references to
prior art.
7. Parts-of-speech.
The vectors of meaning should be predicative definitions, but predicative definitions may not be
the vectors.
The detection of parts-of-speech for words can easily be performed (by computer) using the
method of US Patent 8447789:
a) Words are extracted from each predicative phrase from each clause,
b) For each of the extracted words, a connection to a definition is retrieved from a
dictionary,
c) The definition is always a paragraph;
d) The definition is then profiled the method of US Patent 8504580,
6
Later Mr. Geller proposes to make use of any thematically close to the given, pointed at the same
direction paragraphs of any available texts (US Patent 8516013).
e) The profile of the definition paragraph is then compared, according to an appropriate
compatibility algorithm, to the profile of the paragraph from which the words extracted,
and some surrounding paragraphs,
f) If the algorithm is satisfied, the predicative phrase is vector.
People determine parts-of-speech the same way.
The fact that Geller was granted the US Patent shows that there is no any prior art.
8. Statistics: Weights.
In his US Patent 8504580 Geller proposed the method of Internal weighting7 of vectors: the
weight refers to the frequency that a context phrase occurs in relation to other context phrase. For
instance, there are two sentences:
a) ‘Fire!’
b) ‘In this amazing city of Rome some people sometimes may cry in agony: ‘Fire!’’
Evidently, that the vector ‘Fire!’ has different importance into both sentences, in regard to extra
information in both. This distinction is reflected as the phrase weights: the first has 1, the second
– 0.12; the greater weight signifies stronger emotional ‘acuteness’. The weights are the first ever
internal, essential, from inside text statistics; before Mr. Geller the only way to establish some
kind of statistics were connected with spying, quires, SQL. See for instance the present state of
art into IBM, Oracle, Microsoft, Google an Yahoo? Apache Hadoop and NoSQL?
Remark. In US Patent 6199067 Geller suggested External statistical measure, popularity; where
popularity is the statistics on how predicative definitions are popular among people/ how often
they use them; only Internet can provide this kind of data: obviously, there is no popularity into
databases (see Google’s US Patent 20110040733).
9. Reconstruction.
All one-two words clauses always implicitly refer to omitted words: the implicitly mentioned
words could be restored, based on Geller’s method (Geller 2004). Neither prior art nor new
publications on the preposition ‘in’ – humans add it automatically if they know8.
IV.
Philosophy (of Language).
1. Text.
a) Only text contain causes and consequences at the same time – nobody knows what
shall happen in future, but text does;
b) Text is eternal: only physical foundation of text vanishes, text does not;
c) If text is re-written – it’s a new text, the old one stays forever the same;
d) Text is one of two existing singularities in our Universe – it is absolutely unique, all
copies of it are the same (only their physical foundations are different).
‘Internal’ means that statistic is obtained directly from texts.
In the structure of predicative definitions the adjective/ preposition ‘in-interior’ indicates the familiarity
with what are the issues of definitions.
7
8
Another eternal singularity is quanta of light: light quanta are many and one. Moore called this
phenomenon ‘Identity of Indiscernibles’: how to distinguish the identical, many but the same
photons and identical copies of one and the same text (Moore 1993)? We have a paradox and
phenomenon right before us, which have not been noticed and dealt with in Science.
Text is something ephemeral, transcendental: it does not exist as things and human do.
1. Knowledge.
In Differential Linguistics it’s told that an isolated-separated word is a none-predicative definition
(in Poincare sense) – it is a noun, Knowledge. As soon as the isolated word is incorporated into a
predicative phrase it becomes an opinion. Indeed, previously Geller referred to this example: a
none-predicative definition ‘ggffrrtte’ (Geller 2004). Who can tell what Geller meant by
‘ggffrrtte’ unless it is included in a phrase and, consequently, explained by multiple words and
subtexts?
Moore, in Truth and Falsity wrote on Knowledge: ‘So far, indeed, from truth being defined by
reference to reality, reality can only be defined by reference to truth (Moore 1993)’. Wittgenstein
at 1.1 and 1.3 clarified: ‘The world is the totality of facts, not of things… The facts in logical
space are the world.’ The pillars of Analytical Philosophy divided reality and truth, world and
facts, as Geller divided Knowledge from opinions.
As you can see Russell was confused telling what Knowledge is, as well as all other authors
without a single exception: ‘…knowledge might be defined as belief which is in agreement with
the facts …and no one knows what sort of agreement between them would make a belief true
(Russell 1926).’ Merriam Webster, for instance, is also lost: ‘information, understanding, or skill
that you get from experience or education; awareness of something; the state of being aware of
something’.
Knowledge is Nothing in Hegel’s sense: ‘...pure being is the pure abstraction, and hence it is the
absolutely negative, which when taken immediately, is equal nothing (Hegel 1991). Geller
understands the absence of words, silence as the Knowledge of everything at once (Geller 2005,
Geller 2006). Wittgenstein thought the same: ‘Whereof one cannot speak, thereof one must be
silent’.
Thus, there are two kinds of Knowledge: Knowledge as silence and as none-predicative
definitions. Text is not Knowledge but it is Nothing, though.
Geller thinks that Knowledge is the limit: the function of Knowledge changes its nature as soon
as it reaches the limit. This allowed Geller to use Differential Analyses into (Computational)
Linguistics.
2.
Differential Linguistics.
Out of the given set of all possible Knowledge E, one can relate to an isolated word – let’s call it
x – designated as y=f(x). One can then say that for E a function of Knowledge is provided:
y = f(x), х  Е
According to Geller the function of Knowledge is a differentiable function for which a derivative
from the function y’=f’(x) exists, as paragraph:
Fig. 4
The second derivative y’’ is text.
Remark. It looks like we know and can operate only with integrals (paragraphs), the
function(s) of Knowledge and its argument(s) are inside our brains. We can track the function
only discretely, by the discrete requests for information: sense data9 and other intermediaries
between mind and the Universe exist as consciousness, as electrical-magnetic notions into brain
neurons between internal analyses and external physical acts.
3.
The proofs.
1. Personalization.
Personalization is the selection of right subtexts; they implicitly explain what the words are and
how they explicitly should be used.
2. The first proof.
13 years ago Geller was granted US Patent 6199067, which contains the idea of abovementioned
personalization, as well as on External weights and search for opinions by predicative definitions.
In 2010 Geller got the Summary Judgment, suing Google. Google’s own expert, professor Peters
‘…specifically testified at his deposition that he identified the one major, relevant difference that
he perceived between the prior art and the asserted claims:
Q.
[...] Does your report set forth the differences between any of the asserted claims and the prior
art?
A.
Well, there are very few differences to be honest. The only one that I found that – was the use of
part-of-speech tagging in linguistically profiling users and stored data files and queries for these
purposes, for the purposes of personalized information retrieval. And the report does actually
specifically address that difference (PA Advisors v Google ‘Defendants…’ 2010)’.
As you can see Google uses both Geller’s personalization (Google creates profiles on users,
collecting their subtexts), External weighting and predicative definitions10 (PA Advisors v Google
‘Summary…’ 2010). Chief Judge of the United States Court of Appeals for the Federal Circuit
Randall Rader confirmed it all.
9
Sense data are supposedly mind-dependent objects whose existence and properties are known directly to
us in perception (Russell 1912).
10
Google recently confirmed that: ‘Keywords of two or three words tend to work most effectively.’
https://support.google.com/adwords/answer/2453976?hl=en
Therefore, the first time in History the first ever Humanitarian theory of Differential Linguistics
was firmly confirmed, at 3rd of March, 2010.
3. Other proofs.
In US Patent 8504580 instead of External popularity Geller proposed to use Internal weights11. In
few months after Geller filed the patent application Brin and Page (Google) began to apply his
idea practically, as usual without referencing to Geller’s priority or licensing his technology: ‘The
significance of the subsequent keywords in the list are calculated based on the number of
occurrences of each keyword compared to the number of occurrences of the keyword that appears
most on the site12.’
Having Internal statistics Google is able to establish the internal connections between
advertisements (texts and images) and what Brin and Page call ‘landing pages’ (texts and
images), for Google AdWord and AdSense, as Geller described in his US Patent 8516013.
Consequently, one more new practical and very lucrative development of Differential Linguistics
is provided, by the same notorious Brin and Page.
LexisNexis Semantic Search powered by PureDiscovery™ also applies Internal weights: ‘You
can… assign relative importance (weighting), eliminate concepts you don’t wish to use…13’
IBM as well began to use Internal measure for database: ‘A matching algorithm function that is
called MemScore is used to compare two values and return a score that quantifies the similarity
between the two values14’.
Microsoft does the same: ‘The Bing Adsquality score shows you how competitive your ads are in
the marketplace by measuring how relevant your keywords and landing pages are to customers'
search queries and other input. The quality score can range from 1 to 10, with 10 being the
highest. You can see the quality score on the Keywords, Campaigns, and Ad groups tabs on the
Campaigns page15.’
Please read how it was done before Geller: ‘Frequency of a word or phrase in a particular section times
the manually assigned weight (importance) given to that section. The weights for each word or phrase were
then summed across sections (D'hondt 2013).’
12
http://www.canonicalseo.com/keyword-significance-details-in-google-wmt/
13
LexisNexis began to use Internal weighting at the Fall, 2009 after Geller applied for his US Patent
8504580: http://www.lexisnexis.com/en-us/about-us/media/pressrelease.page?id=125674399689744#sthash.LjjwhaI0.dpuf
14
For instance, IBM, some time ago: ‘You can define specific terms or multi-word terms that raise or lower
the rank value of the document in which the term appears. Each term in the boost dictionary is associated
with a boost factor that can range from -10 to +10.’
http://pic.dhe.ibm.com/infocenter/analytic/v3r0m0/index.jsp?topic=%2Fcom.ibm.discovery.es.ta.doc%2Fii
ysaboostwrds.htm and IBM now: http://www01.ibm.com/support/knowledgecenter/SSWSR9_11.4.0/com.ibm.swg.im.mdmhs.policyhub.doc/topics/data
_quality_scores.html?lang=en
15
http://advertise.bingads.microsoft.com/en-us/help-topic/how-to/50813/what-is-my-quality-score-andwhy-does-it-matter
11
Hewlett Packard and SAP do use Geller’s Internal measure as well as well as the presented here
Hierarchy of languge16.
There is no other way to get Internal weights as using abovementioned Geller’s hierarchy. For
instance, the phrase ‘amazing Rome in agony’ makes no sense, considering the above example:
phrases must be obtained in regard to their clauses.
4. US patent 8504580: another proof.
The same US patent 8504580 contains the idea of searching for information based on paragraphs.
Indeed, search for whole text rarely makes sense because one and the same text may concentrate
on many not wanted topics; it’s better to search for one and specific theme.
Eight days after17 Geller filed the patent Google told that it began showing ads in a form of
advertising known as behavioral targeting18. Before Geller formulated and published his
Differential Linguistics and his patent applications nobody, including Brin and Page, searched for
paragraphs because it’s not possible without Internal weights. (To obtain weights it is the absolute
must to get phrases from clauses but Geller has the patent.)
Google behavioral targeting is another capital proof for Geller’s Differential Linguistics.
VII.
Discussion.
1. Geller found that Linguistics should use Set Theory and Differential Analyze.
2. Geller discovered how the only hierarchy of language looks like: it’s the hierarchy of
sets.
3. Geller discovered that the limit for the function of Knowledge is only one, singular
Knowledge.
4. The problem of Identity of Indiscernibles can find its solution in the assumption that there
are two kinds of Nothingness and text is the third.
5. As for Humanities – they have become exact Science, as Geller declared into 2004:
everything concerning consciousness and cognition can easily be fixed, measured and
evaluated (Geller 2004). Actually, Google and other Internet companies do this for years.
6. Geller finished what Poincare, Russell, Wittgenstein and More started.
VIII.
Conclusion.
Many problems of Philosophy and Linguistics are ultimately resolved.
16
http://www.autonomy.com/technology/idol-functions/conceptual-search and
http://help.sap.com/hana/SAP_HANA_Text_Mining_Developer_Guide_en.pdf
17
Patent Reform Act of 2009 switched U.S. patent priority from the existing ‘first-to-invent’ system to a
‘first-to-file’.
18
New York Times at http://www.nytimes.com/2009/03/11/technology/internet/11google.html?_r=4& and
‘…we recommend including more text-based content about these topics, including complete sentences and
paragraphs, to assist our crawlers in gathering information about your pages and determining relevant ads
to display.’ https://support.google.com/adsense/answer/32844?hl=en&ref_topic=1628432
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