The algorithmically minded will have noticed that paging requires associative array (like Java Map of Python dict()) abstract data structure where:
  • the keys are linear pages addresses, thus of integer type
  • the values are physical page addresses, also of integer type
The single level paging scheme uses a simple array implementation of the associative array:
  • the keys are the array index
  • this implementation is very fast in time
  • but it is too inefficient in memory
and in C pseudo-code it looks like this:
linear_address[0]      = physical_address_0
linear_address[1]      = physical_address_1
linear_address[2]      = physical_address_2
...
linear_address[2^20-1] = physical_address_N
But there another simple associative array implementation that overcomes the memory problem: an (unbalanced) k-ary tree.
A K-ary tree, is just like a binary tree, but with K children instead of 2.
Using a K-ary tree instead of an array implementation has the following trade-offs:
  • it uses way less memory
  • it is slower since we have to de-reference extra pointers
In C-pseudo code, a 2-level K-ary tree with K = 2^10 looks like this:
level0[0] = &level1_0[0]
    level1_0[0]      = physical_address_0_0
    level1_0[1]      = physical_address_0_1
    ...
    level1_0[2^10-1] = physical_address_0_N
level0[1] = &level1_1[0]
    level1_1[0]      = physical_address_1_0
    level1_1[1]      = physical_address_1_1
    ...
    level1_1[2^10-1] = physical_address_1_N
...
level0[N] = &level1_N[0]
    level1_N[0]      = physical_address_N_0
    level1_N[1]      = physical_address_N_1
    ...
    level1_N[2^10-1] = physical_address_N_N
and we have the following arrays:
  • one directory, which has 2^10 elements. Each element contains a pointer to a page table array.
  • up to 2^10 pagetable arrays. Each one has 2^10 4 byte page entries.
and it still contains 2^10 * 2^10 = 2^20 possible keys.
K-ary trees can save up a lot of space, because if we only have one key, then we only need the following arrays:
  • one directory with 2^10 entries
  • one pagetable at directory[0] with 2^10 entries
  • all other directory[i] are marked as invalid, don't point to anything, and we don't allocate pagetable for them at all
Video 1.
GraphRAG: The Marriage of Knowledge Graphs and RAG by Emil Eifrem
. Source.
Video 2.
The Future of Knowledge graphs in a World of LLMs by Denny Vrandečić
. Source.
This is one of those idealistic W3C specifications with super messy implementations all over.
SPARQL tutorial by Ciro Santilli 40 Updated 2025-07-16
In this tutorial, we will use the Jena SPARQL hello world as a starting point. Tested on Apache Jena 4.10.0.
Basic query on rdf/vcard.ttl RDF Turtle data to find the person with full name "John Smith":
sparql --data=rdf/vcard.ttl --query=<( printf '%s\n' 'SELECT ?x WHERE { ?x <http://www.w3.org/2001/vcard-rdf/3.0#FN> "John Smith" }')
Output:
---------------------------------
| x                             |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------
To avoid writing http://www.w3.org/2001/vcard-rdf/3.0# a billion times as queries grow larger, we can use the PREFIX syntax:
sparql --data=rdf/vcard.ttl --query=<( printf '%s\n' '
PREFIX vc: <http://www.w3.org/2001/vcard-rdf/3.0#>
SELECT ?x
WHERE { ?x vc:FN "John Smith" }
')
Output:
---------------------------------
| x                             |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------
Bibliography:
The CLI tools don't appear to be packaged for Ubuntu 23.10? Annoying... There is a package libapache-jena-java but it doesn't contain any binaries, only Java library files.
To run the CLI tools easily we can download the prebuilt:
sudo apt install openjdk-22-jre
wget https://dlcdn.apache.org/jena/binaries/apache-jena-4.10.0.zip
unzip apache-jena-4.10.0.zip
cd apache-jena-4.10.0
export JENA_HOME="$(pwd)"
export PATH="$PATH:$(pwd)/bin"
and we can confirm it works with:
sparql -version
which outputs:
Apache Jena version 4.10.0
If your Java is too old then then running sparql with the prebuilts fails with:
Error: A JNI error has occurred, please check your installation and try again
Exception in thread "main" java.lang.UnsupportedClassVersionError: arq/sparql has been compiled by a more recent version of the Java Runtime (class file version 55.0), this version of the Java Runtime only recognizes class file versions up to 52.0
        at java.lang.ClassLoader.defineClass1(Native Method)
        at java.lang.ClassLoader.defineClass(ClassLoader.java:756)
        at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
        at java.net.URLClassLoader.defineClass(URLClassLoader.java:473)
        at java.net.URLClassLoader.access$100(URLClassLoader.java:74)
        at java.net.URLClassLoader$1.run(URLClassLoader.java:369)
        at java.net.URLClassLoader$1.run(URLClassLoader.java:363)
        at java.security.AccessController.doPrivileged(Native Method)
        at java.net.URLClassLoader.findClass(URLClassLoader.java:362)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
        at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
        at sun.launcher.LauncherHelper.checkAndLoadMain(LauncherHelper.java:621)
Build from source is likely something like:
sudo apt install maven openjdk-22-jdk
git clone https://github.com/apache/jena --branch jena-4.10.0 --depth 1
cd jena
mvn clean install
TODO test it.
If you make the mistake of trying to run the source tree without build:
git clone https://github.com/apache/jena --branch jena-4.10.0 --depth 1
cd jena
export JENA_HOME="$(pwd)"
export PATH="$PATH:$(pwd)/apache-jena/bin"
it fails with:
Error: Could not find or load main class arq.sparql
as per: users.jena.apache.narkive.com/T5TaEszT/sparql-tutorial-querying-datasets-error-unrecognized-option-graph
Once you've done the Apache Jena CLI tools setup we can query all users with Full Name (FN) "John Smith" directly fom the rdf/vcard.ttl Turtle RDF file with the rdf/vcard.rq SPARQL query:
sparql --data=rdf/vcard.ttl --query=rdf/vcard.rq
and that outputs:
---------------------------------
| x                             |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------
WordNet by Ciro Santilli 40 Updated 2025-07-16
Groups concepts by hyponymy and hypernymy and meronymy and holonymy. That actually makes a lot of sense! TODO: is there a clear separation between hyponymy and meronymy?
Browse: wordnetweb.princeton.edu/perl/webwn Appears dead as of 2025 lol.
The online version of WordNet has been deprecated and is no longer available.
Does not contain intermediat scientific terms, only very common ones, e.g. no mention, of "Josephson effect", "photoelectric effect"

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact