
Ask HN: Perspectives on graph-bound logical inference - wll
I am researching graph processing (OLTP) and graph databases for a system where semanticity is inherent.<p>I am currently exploring logical inference (or reasoning) (Stardog [1], GraphDB [2], Grakn [3]) and stumbled upon «The Semantic Web, Syllogism, and Worldview» (2003) [0].<p>Semantics aside (this system would mandate for Stardog and Grakn’s lazy reasoning rather than GraphDB’s total materialization), I am interested in practical analyses of logical inference as I find some [0] arguments to be sound and atemporal and am therefore “undirected.”<p>Although it does not support automatic reasoning, Datomic [4] viewpoints are welcome.
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wll
[0]
[http://web.archive.org/web/20180311022804/http://www.shirky....](http://web.archive.org/web/20180311022804/http://www.shirky.com/writings/herecomeseverybody/semantic_syllogism.html)

[1]
[https://www.stardog.com/docs/#_owl_rule_reasoning](https://www.stardog.com/docs/#_owl_rule_reasoning)

[2]
[http://graphdb.ontotext.com/documentation/enterprise/reasoni...](http://graphdb.ontotext.com/documentation/enterprise/reasoning.html)

[3] [http://dev.grakn.ai/docs/knowledge-
model/inference](http://dev.grakn.ai/docs/knowledge-model/inference)

[4] [https://docs.datomic.com/on-prem/query.html](https://docs.datomic.com/on-
prem/query.html)

