I think  I were slightly not very focused today and couldnt study very focused today.

I were kind of lazy today.


But I were studying last hours but not with very high focus. 

But I think this second semester content, I check chapters of randomly, this is not a blocker for expressivity capability for the very initial version of topology RDF/grammar version and knowing that I had a thought in my mind saying lets go check sage/start defining RDF/grammar initial version (which would be silly initially) so also due to such inner thought I couldnt focus well to semester 2 chapters in last hours even had studied slightly. Its not something that is very necessary for expressivity power of initial RDF/topology so I  were instead last hours curious to start actually task of RDF definition most. 


yayyy so its 1:30am and now its time to start the curious topology RDF/grammar definition task. 

hmm the conversion of PTB and graph structures to this RDF would be one very curious task imho. 


hmm first algebraic linguistic task investigation is how to define pronouns in such topology RDF/grammar? :D


first curious task of algebraic linguistic studies. 

hmm so initial task of RDF design starts actually from RDF's correspondence to linguistics side.

So initial task is defining prononuns conceptual correspondent concepts in RDF side that would be alike type study of algebraic linguistics.


Hmm I give up now for today this very initial and very crucial task and would intend to solve tomorrow.

I slightly checked /read also chapters of semester 2 today. not all but some. 

hmm I think this is the first task.


of PTB translation to algebraic linguistics correspondent RDF structures.

I have initial idea of the RDF constructs coming from group theory/abstract algebra/topology.


but even before that I think its crucial to define this translation mechanism from linguistics PTB side and wordnet semantics side to algebraic definitions side.

Its even if I had not studied representation theory, its slightly similar task/study. 

So after initial semester ended and second semester slightly studied to, (not fully yet, I lacked focus today) first task of study becomes e representation theory alike task. 


Lets also mention that, for such an ai, defining an algebraic linguistic study is not necessary. I mean you dont have to build an algebraic representation to linguistics side to build any ai that would interpret.

But, I have such objective. even not very crucial nor very necessary for such an ai project. I wish such correspondence and some algebraic inference mechanisms also be applicable to linguistics side. even of course this is not a mandatory thing to do when building an ai. its rather my own design principle is like this and it had not had to be necessarily like this either. noone needs to build an algebraic linguistics modules /translations to build an intelligent ai. there is no such mandatory necessity. but I wish to follow such design principles. I wish to setup algebraic correspondence. 


but today feeling now tired. I would resume this very curious task of representation theory alike task tomorrow. hmm might first try to solve this task myself initially then might also check representation theory to check an example of. 

this is kind of over doing reductionism/ cartesian  approaches. right? I mean my obsession to do translate to algebraic RDF side. but I want the clarify of definition even with ambuigities of with algebraic structures. I want reductionism/carteisan approach be very strictly present specifically for this side. plus of course the conceptual ontological hierachies levels /ontology instances would be also predicted by neural nets but beside they would have this algebraic definition wise definitions set. I just want that: e.g. go verb --> means an isometric transformation or rigid motion from some place to other but not any simple as this, the homomorphism and their sets would be elaborate. Its not decided to how to design these yet. tomorrow would be decided. I could even use polynomial rings even. I mean there is no design decisions yet. tomorrow, I would study polynomial chapter also but then also revise some topics to decide these RDF translated patterns that would be used to translate language to. 

first task as mentioned is how to design pronouns algebraically. 

as mentioned I might first try to solve myself  with checking this abstract algebra book. as a study or like homework task to me in this course of abstract algebra.  i mean for this course, my first task is applicance of abstract aglebra to define the pronouns of linguistics side in algebraic domain. this i would try to solve myself. I am sure I would come up with some solution options. but finally at the end, I would go over representation theory to see if it is solving it and if it solves more adequately to utilize that and beside it might also improvise new approaches to solve this homework. 

So I crafted such homework or exam to myself for this abstract algebra course I studied. 


hmm than it would be coded in ai studies to convert dependency structures PTB Entities to topology RDF/grammar translated definitions as a knowledge graph defined with such RDF/grammar(algebraic/topology based RDF/grammar that its design studies started tonight and first task started with translation correspondences for pronouns concept of linguistics). 

I think I would rest now.

yayyy tomorrow would be a lot fun. since this initial task is very puzzle alike homework/exam. 

(I liked puzzle like homeworks when doign Bsc in computer engineering field, our homeworks most of the time were like puzzling/puzzle alike and I liked that. so it would be slightly like nostalgia to solving computer engineering homeworks (Ceng course homework, always were like a puzzle) ) 

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ayyy I am so happy to have extended my very ignorant linguistics knowledge just due to curiosity via Sumerian language studies initialization sometime this last year to understand see a sample of linguistics universe to get to know that even theoretically language's formal context free grammar even is theoretically unbounded, existing language patterns and their initial written language versions (e.g. Sumerian) is a set that is bounded by practical sets of language patterns. I mean its not unreasonable to plan a study to convert even verbs to algebraic definitions and span synonyms hypternyms via supervised/semi supervised methodologies that its possible to accomplish this algebraic definitions translation task in a reasonable time frame/project plan (without exceeding the november deadline of 1.0 ai version) 

hmm most crucial verbs (e.g. go.  I think one most crucial verb is go verb)  would be converted also even in 0.1 ai version. 

this is not just these also parse trees similarly would be translated to algebraic representations in topology  RDF/grammar. all PTB tags etc etc/spans/dependency graphs all infoprmation would be translated to topology grammar/RDF.



lets see my obsessive design bias to Cartesianism is a good thing  or not :) 

I know when we say ai, we dont necessarily mean Cartesianism but more nominalism. 

But I either living in vicinity of century of positivism, have a strong bias to follow positivist cartesianist design principles. 

I think its because its easier to control knowledge graphs if its managed carteisan /reductionist alike. 

otherwise if it were full neural networks with no connection to semantics knowledge graphs it would be not possible to verify whether ai is interpreting correct or whether is not. I feel slightly incongruent of this design bias I have of positivist design bias design traditions with cartesian methods whilst we have gone over positivist centuries and now in post modernist world, this much obsession to build with cartesian design principles has a slight noncongruency feeling of feeling like following outdated methodologies. but I cant design otherwise method. I obsessively design like this because it wont be possible to verify whether if ai interprets correctly in otherwise. and thats the crucial thing since this ai would/is built to do science autonomously. thereby its very crucial to be able to easily check if it could interpret correctly.  full neural network approaches dont have such verification methods easily.  though I know positivist approach is outdated I have no alternative right now. maybe ai itself could devise later itself a full neural network based ai systems but I can not devise it. 
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One funny aspect/laughes topic  :D

this approach of assesing linguistics topics via math were first tried in medieval times :D


so dont think i am creating a very new paradigm in linguistics. :D  I thought I were creating a new paradigm 1 year ago or more ago and then those times, when saw that my approach were,  not exactly of same approach, but similar intents in linguistics had been even attempted to be built even in medieval times so I laughed alot:D (laughed alot to me wrongly assumming I were creating a new paradigm there/here :D nah :DDDDDDDDDDDD) 

(even mathematical approaches in linguistics never take the hype/never became popular, they were even existing in medieval times :D so I am surely not any inventing any thing new :D and thats very funny to  think being inventing a new approach and seeing it even existed in medieval times :DDDDDDD) 


by then I were studying to philosophy of linguistics. I still know not much about linguistics. but knowing necessary enough to build ai projct, I think I gathered enough knowledge for that. though, of course, I am very ignorant in linguistics still. but one does not need to be a very expert in linguistics to build this type of ai proejct. (ai of autonomous science capabilities, it wont be a language excelling type ai, but it would have capability to interpret particle physics books alike books it reads etc. its rather type ai project of: assisted autonomous science building capabilities. ) 

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