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(Q54871) (Q3428776) for (Q5) - SPARQL Queries for Humans is my M.Sc. C.S. Thesis project.

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SPARQL for Humans

Paper
https://aidanhogan.com/docs/sparql-autocompletion.pdf

Using this repository

You will first need a Wikidata dump.

Wikidata Dump

Then some tools for compiling the source code.

Development tools

Git For Windows SDK since need an update version of gzip to sort the large output files

If your planning on running the benchamarks only, then node is not required.

Set up gzip

On the Git SDK-64 console (Git for Windows SDK Console)
Install gzip via pacman

$ pacman -S gzip

We'll now need to clone the repository and build the project.

Clone and build

On the Git SDK-64 console

$ git clone https://github.com/gabrieldelaparra/SPARQLforHumans.git

> Cloning into 'SPARQLforHumans'...
> [...]

$ cd SPARQLforHumans

$ dotnet build .

> [...]
> Build succeeded.
>     0 Warning(s)
>     0 Error(s)

Now we will run some tests to check that everything works.

Test

$ cd SparqlForHumans.UnitTests/

$ dotnet test

> [...]
> Passed!  - Failed:     0, Passed:   214, Skipped:     0, Total:   214, Duration: 9 s - SparqlForHumans.UnitTests.dll (netcoreapp3.1)

If any of the tests do not pass, you can create an issue and I will get in touch with you :)
Now we will run the Command Line Interface to filter and index our Wikidata dump.

Command line interface

$ cd ../SparqlForHumans.CLI/

$ dotnet run -- --version
> SparqlForHumans.CLI 1.0.0

For the following sections a given Sample500.nt file is given on the root folder of the repository.
To build the complete index (production), latest-truthy.nt.gz should be used.

Note that filtering, sorting and indexing the latest-truthy.nt.gz will take ~40 hours, depending on your system.

Filter

Filters an input file:

  • Keeps all subjects that start with http://www.wikidata.org/entity/
  • Keeps all predicates that start with http://www.wikidata.org/prop/direct/
    • and object starts with http://www.wikidata.org/entity/
  • or predicate is label, description or alt-label
    • and object is literal and ends with @en.

These can be changed on the SparqlForHumans.RDF\FilterReorderSort\TriplesFilterReorderSort.IsValidLine() method.

To filter run:

$ dotnet run -- -i ../Sample500.nt -f

The command for sorting is given in the console after filtering.
It will add the .filterAll.gz sufix as filtered output and .filterAll-Sorted.gz for sorting.

Filter for latest takes ~10 hours on my notebook computer (16GB RAM).

Sort

Sorting takes Sample500.filterAll.gz as input and outputs Sample500.filterAll-Sorted.gz.

The sorting command process gives no notifications about the status.
Sorting latest takes ~5 hours and requires 3x the size of Filtered.gz disk space (~40GB free for latest)

$ gzip -dc Sample500.filterAll.gz | LANG=C sort -S 200M --parallel=4 -T tmp/ --compress-program=gzip | gzip > Sample500.filterAll-Sorted.gz

Entities Index

After filtering and sorting, we can now create our index. As a note, both "-e -p" can be given together for the sample file to generate both Entities and Properties Index. For a large file, it is better to do them in 2 steps.

Entities Index will be created by default at %homepath%\SparqlForHumans\LuceneEntitiesIndex\

$ dotnet run -- -i Sample500.filterAll-Sorted.gz -e

If -p was not used above, then we need to create the Properties Index.

Building the Entities Index takes ~30 hours to complete.

Properties Index

$ dotnet run -- -i Sample500.filterAll-Sorted.gz -p

Properties Index will be created by default at %homepath%\SparqlForHumans\LucenePropertiesIndex\

Now our index is ready.

  • We can now run our backend via SparqlForHumans.Server/ using the RDFExplorer client.
  • Or recreate the results from the paper via SparqlForHumans.Benchmark/.

Building the Properties Index takes ~2 hours to complete.

Run Server

The backend will listen to request from a modified version of RDFExplorer. First we will need to get the server running:

$ cd ../SparqlForHumans.Server/

$ dotnet run

With the server running we can now start the client.

Run Client: RDFExplorer

We will now need another console for this.

$ cd `path-for-the-client`

$ git clone https://github.com/gabrieldelaparra/RDFExplorer.git

$ cd RDFExplorer

$ npm install

$ npm start

Now browse to http://localhost:4200/

Compare against the Wikidata Endpoint

With the full index we can compare our results agains the Wikidata Endpoint.

  • 67 Properties ({Prop}) have been selected to run 4 type of queries (For a total of 268)
    • ?var1 {Prop} ?var2 . ?var1 ?prop ?var3 .
    • ?var1 {Prop} ?var2 . ?var3 ?prop ?var1 .
    • ?var1 {Prop} ?var2 . ?var2 ?prop ?var3 .
    • ?var1 {Prop} ?var2 . ?var3 ?prop ?var2 .
  • 268 queries are run against our Local Index and the Remote Endpoint.
  • We will query for ?prop on both (Local and Remote) and compare the results.
  • Running the benchmarks takes 2~3 hours, due to the 50 seconds timeout if the query cannot be completed on the Wikidata Endpoint.
  • The details of the runs will be stored at benchmark.json.
  • The time results will be summarized at results.txt.
  • The time results, for each query, will be exported to a points.csv. Each row is a query. The Id of the query can be found on the benchmark.json file as HashCode.
  • A qualitative comparison (precision, recall, f1), for each query, will be exported to metrics.csv. Each row is a query. This will only consider those queries that returned results on the Remote Wikidata Endpoint.
$ cd ../SparqlForHumans.Benchmark/

$ dotnet run

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(Q54871) (Q3428776) for (Q5) - SPARQL Queries for Humans is my M.Sc. C.S. Thesis project.

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