My experiments use only a specialized language similar to natural language in many respects (unlike XML, OWL, etc.), but is certainly not natural. It seems to me that it is possible to use natural language by defining a set of rules for translating phrases in natural language into a set of statements in an implemented formal language and rules for the reverse transformation - with the rules being formulated in this implemented formal language; however, I have not attempted to do this.
The placement of cat in the Venn diagram suggests that all cats are pets. I think the placement needs to move to a position over the pet boundary. This will indicate that some cats are pets and some are not. Further, I imagine that the Venn diagram suggests that not all relations reduce to 'is' because 'is' infers an affirmative positive semantic; whereas we also need affirmative negative semantic ('is not') to complete our understanding; noting that the absence of 'is' is insufficient to infer 'is not' and will only produce an unknown.
You`re right about the cat; I implicitly mean "home cat".
Our semantic graph is not a just-another-representation of the Venn diagram (probably it should be emphasized); in the case of the Venn diagram relation "is" is definitely transitive, but in our Semantic Graph transitivity is an optional attribute, and the absence of the "IS" means exactly "unknown if it is" (that resembles human convention). Relation "not is" can be constructed like any other relation using the concept "NOT".
Communication language (will be described later) used in our approach includes syntactic negation.
This is highly aligned with my independent work and thinking, Mykola.
Is there a set of NLP algorithms or methods you have found most suitable for ontology engineering and/or semantic decomposition?
My experiments use only a specialized language similar to natural language in many respects (unlike XML, OWL, etc.), but is certainly not natural. It seems to me that it is possible to use natural language by defining a set of rules for translating phrases in natural language into a set of statements in an implemented formal language and rules for the reverse transformation - with the rules being formulated in this implemented formal language; however, I have not attempted to do this.
The placement of cat in the Venn diagram suggests that all cats are pets. I think the placement needs to move to a position over the pet boundary. This will indicate that some cats are pets and some are not. Further, I imagine that the Venn diagram suggests that not all relations reduce to 'is' because 'is' infers an affirmative positive semantic; whereas we also need affirmative negative semantic ('is not') to complete our understanding; noting that the absence of 'is' is insufficient to infer 'is not' and will only produce an unknown.
Thank you for your comment!
You`re right about the cat; I implicitly mean "home cat".
Our semantic graph is not a just-another-representation of the Venn diagram (probably it should be emphasized); in the case of the Venn diagram relation "is" is definitely transitive, but in our Semantic Graph transitivity is an optional attribute, and the absence of the "IS" means exactly "unknown if it is" (that resembles human convention). Relation "not is" can be constructed like any other relation using the concept "NOT".
Communication language (will be described later) used in our approach includes syntactic negation.
This is parallel to my work.
Let's connect.
https://physix.world/
This is parallel to my work.
Let's connect.
https://physix.world/