Awesome

simple-wikidata-db

This library provides a set of scripts to download the Wikidata dump, sort it into staging files, and query the data in these staged files in a distributed manner. The staging is optimized for (1) querying time, and (2) simplicity.

This library is helpful if you'd like to issue queries like:

Fetch all QIDs which are related to Q38257
Fetch all triples corresponding to the relation (e.g. P35)
Fetch all aliases for a QID

Downloading the dump

A full list of available dumps is available here. To fetch the most recent dump, run:

wget https://dumps.wikimedia.org/wikidatawiki/entities/latest-all.json.gz

or, if aria2c is installed, run:

aria2c --max-connection-per-server 16 https://dumps.wikimedia.org/wikidatawiki/entities/latest-all.json.gz

Downloading takes about 2-5 hours (depending on bandwidth).

Processing the dump

The original downloaded wikidata dump is a single file and combines different types of information (alias names, properties, relations, etc). We preprocess the dump by iterating over the compressed file, and saving information to different subdirectories. For more information, see the Data Format. To preprocess the dump, run:

python3 preprocess_dump.py \ 
    --input_file $PATH_TO_COMPRESSED_WIKI_JSON \
    --out_dir $DIR_TO_SAVE_DATA_TO \
    --batch_size $BATCH_SIZE \
    --language_id $LANG

These arguments are:

input_file (required): path to the compressed JSON Wikidata dump json file
out_dir (required): path to directory where tables will be written. Subdirectories will be created under this directory for each table.
num_lines_read (default: -1): number of lines to read. Useful for debuggin.
num_lines_in_dump (default: -1): specifies the total number of lines in the uncompressed json file. This is used by a tqdm bar to track progress. As of January 2022, there are 95,980,335 lines in latest-all.json. It takes about ~21 minutes to run wc -l latest-all.json.
batch_size (default: 10000): The number of triples to write into each batch file that is saved under a table directory.
language_id (default 'en'): The language to use when extracting entity labels, aliases, descriptions, and wikipedia links

To do an initial verification of the pipeline, specify a small num_lines_read like 100. This should finish in less than a second.

Providing num_lines_in_dump will provide a progress bar.

It takes ~5 hours to process the dump when running with 90 processes on a 1024GB machine with 56 cores. A tqdm progress bar should provide a more accurate estimate while data is being processed.

Data Format

The Wikidata dump is made available as a single, unweildy JSON file. To make querying/filtering easier, we split the information contained in this JSON file into multiple tables, where each table contains a certain type of information. The tables we create are described below:

Table name	Table description	Table schema
labels	Holds the labels for different entities	qid: the QID of the entity <br> label: the entity's label ('name')
descriptions	Holds the descriptions for different entities	qid: the QID of the entity <br> description: the entity's description (short summary at the top of the page)
aliases	Holds the aliases for different entities	qid: the QID of the entity <br> alias: an alias for the entity
entity_rels	Holds statements where the value of the statement is another wikidata entity	claim_id: the ID for the statement <br> qid: the ID for wikidata entity <br> property_id: the ID for the property <br> value: the qid for the value wikidata entity
external_ids	Holds statements where the value of the statement is an identifier to an external database (e.g. Musicbrainz, Freebase, etc)	claim_id: the ID for the statement <br> qid: the ID for wikidata entity <br> property_id: the ID for the property <br> value: the identifier for the external ID
entity_values	Holds statements where the value of the statement is a string/quantity	claim_id: the ID for the statement <br> qid: the ID for wikidata entity <br> property_id: the ID for the property <br> value: the value for this property
qualifiers	Holds qualifiers for statements	qualifier_id: the ID for the qualifier <br> claim_id: the ID for the claim being qualified <br> property_id: the ID for the property <br> value: the value of the qualifier
wikipedia_links	Holds links to Wikipedia items	qid: the QID of the entity <br> wiki_title: link to corresponding wikipedia entity

<br><br> Each table is stored in a directory, where the content of the table is written to multiple jsonl files stored inside the directory (each file contains a subset of the rows in the table). Each line in the file corresponds to a different triple. Partitioning the table's contents into multiple files improves querying speed--we can process each file in parallel.

Querying scripts

Two scripts are provided as examples of how to write parallelized queries over the data once it's been preprocessed:

fetching/fetch_with_name.py: fetches all QIDs which are associated with a particular name. For example: all entities associated with the name 'Victoria', which would inclue entities like Victoria Beckham, or Victoria (Australia).
fetching/fetch_with_rel_and_value.py: fetches all QIDs which have a relationship with a specific value. For example: all triples where the relation is P413 and the object of the relation is Q622747.

Other helpful resources:

Getting the full list of properties: https://github.com/maxlath/wikidata-properties-dumper

For any questions or feedback, contact Neel Guha at nguha@cs.stanford.edu