treeedb
NMT4RDFS
| treeedb | NMT4RDFS | |
|---|---|---|
| 1 | 1 | |
| 50 | 9 | |
| - | - | |
| 7.9 | 10.0 | |
| 15 days ago | about 5 years ago | |
| Rust | Python | |
| MIT License | MIT License |
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treeedb
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GDlog: A GPU-Accelerated Deductive Engine
https://github.com/topics/datalog?l=rust ... Cozo, Crepe
Crepe: https://github.com/ekzhang/crepe :
> Crepe is a library that allows you to write declarative logic programs in Rust, with a Datalog-like syntax. It provides a procedural macro that generates efficient, safe code and interoperates seamlessly with Rust programs.
Looks like there's not yet a Python grammar for the treeedb tree-sitter: https://github.com/langston-barrett/treeedb :
> Generate Soufflé Datalog types, relations, and facts that represent ASTs from a variety of programming languages.
Looks like roxi supports n3, which adds `=>` "implies" to the Turtle lightweight RDF representation: https://github.com/pbonte/roxi
FWIW rdflib/owl-rl: https://owl-rl.readthedocs.io/en/latest/owlrl.html :
> simple forward chaining rules are used to extend (recursively) the incoming graph with all triples that the rule sets permit (ie, the “deductive closure” of the graph is computed).
ForwardChainingStore and BackwardChainingStore implementations w/ rdflib in Python: https://github.com/RDFLib/FuXi/issues/15
Fast CUDA hashmaps
Gdlog is built on CuCollections.
GPU HashMap libs to benchmark: Warpcore, CuCollections,
https://github.com/NVIDIA/cuCollections
https://github.com/NVIDIA/cccl
https://github.com/sleeepyjack/warpcore
/? Rocm HashMap
DeMoriarty/DOKsparse:
NMT4RDFS
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GDlog: A GPU-Accelerated Deductive Engine
https://www.researchgate.net/figure/Parameter-Settings-of-th...
"Deep learning for noise-tolerant RDFS reasoning" (2018) > NMT4RDFS: http://www.semantic-web-journal.net/content/deep-learning-no... :
> This paper documents a novel approach that extends noise-tolerance in the SW to full RDFS reasoning. Our embedding technique— that is tailored for RDFS reasoning— consists of layering RDF graphs and encoding them in the form of 3D adjacency matrices where each layer layout forms a graph word. Each input graph and its entailments are then represented as sequences of graph words, and RDFS inference can be formulated as translation of these graph words sequences, achieved through neural machine translation. Our evaluation on LUBM1 synthetic dataset shows 97% validation accuracy and 87.76% on a subset of DBpedia while demonstrating a noise-tolerance unavailable with rule-based reasoners.
NMT4RDFS: https://github.com/Bassem-Makni/NMT4RDFS
...
A human-generated review article with an emphasis on standards; with citations to summarize:
"Why do we need SWRL and RIF in an OWL2 world?" [with SPARQL CONSTRUCT, SPIN, and now SHACL]
What are some alternatives?
gdlog
pydatalog - Fork of pyDatalog https://sites.google.com/site/pydatalog/
warpcore - A Library for fast Hash Tables on GPUs
roxi - Reactive Reasoning
ascent - logic programming in Rust
virtuoso-opensource - Virtuoso is a high-performance and scalable Multi-Model RDBMS, Data Integration Middleware, Linked Data Deployment, and HTTP Application Server Platform
cccl - CUDA C++ Core Libraries
FuXi - Chimezie Ogbuji's FuXi reasoner. NON-FUNCTIONING, RETAINED FOR ARCHIVAL PURPOSES. For working code plus version and associated support requirements see: