There are many applications of Semantic Web that has little to do with natural languages. If you have a better option for all the existing RDF data sets (https://lod-cloud.net/, https://www.wikidata.org/) and ontologies (http://www.ontobee.org/, https://schema.org/) it would be good to be explicit about it.
I would prefer to have more data (e.g. data from US federal reserve data, world bank data) as RDF and accessible via SPARQL endpoints than less, because it is much more useful as RDF than as CSV, in my opinion.
Its "easy" to write some logic rules to parse input text for a 50% demo. But then you want to improve & scale, and suddenly all the nuances, bites you. The rules get bigger, nested and complicated. Traditional NLP tried that avenue for a while, with decent success in small usecases, but for larger problems without success. (Compared to stuff like BERT & GPT, which still have a lot of problems)
Similar with Knowledge Graphs, you can show some nice properties on inferring knowledge on small problems, but the real world is much more approximate and unclear than some (binary) relationships.
Personally i think we Humans lack the mental capacity to build large models with complex interactions.