While I'm on the subject, I would like to draw attention to the Neckar
project <http://event.ifi.uni-heidelberg.de/?page_id=532>, which aims
precisely to classify Wikidata entities in people, places and
organizations. Frequently updated Json dumps are available.

2017-10-16 16:08 GMT+02:00 Ettore RIZZA <[email protected]>:

> @Antonin : Thanks for this counting method, it seems very effective (I
> already knew that there were 3.6 M of humans (Q5) in Wikidata).
>
> https://query.wikidata.org/#%23compter%20le%20nombre%20d%
> 27%C3%A9l%C3%A9ments%20appartenant%20%C3%A0%20la%20cat%C3%A9gorie%0A%
> 23organisation%20ou%20%C3%A0%20ses%20enfants%0ASELECT%
> 20DISTINCT%20%28COUNT%28DISTINCT%20%3Fitem%29%20AS%
> 20%3Fcount%29%20WHERE%20%7B%20%3Fitem%20%28wdt%3AP31%
> 2Fwdt%3AP279%2a%29%20wd%3AQ5.%20%7D
>
> 2017-10-16 15:34 GMT+02:00 Antonin Delpeuch (lists) <
> [email protected]>:
>
>> And… my own count was wrong too, because I forgot to add DISTINCT in my
>> query (if there are multiple paths from the class to "organization
>> (Q43229)", items will appear multiple times).
>>
>> So, I get 1 168 084 now.
>> http://tinyurl.com/yaeqlsnl
>>
>> It's easy to get these things wrong!
>>
>> Antonin
>>
>> On 16/10/2017 14:16, Antonin Delpeuch (lists) wrote:
>> > Thanks Ettore for spotting that!
>> >
>> > Wikidata types (P31) only make sense when you consider the "subclass of"
>> > (P279) property that we use to build the ontology (except in a few cases
>> > where the community has decided not to use any subclass for a particular
>> > type).
>> >
>> > So, to retrieve all items of a certain type in SPARQL, you need to use
>> > something like this:
>> >
>> > ?item wdt:P31/wdt:P279* ?type
>> >
>> > You can also have other variants to accept non-truthy statements.
>> >
>> > Just with this truthy version, I currently get 1 208 227 items. But note
>> > that there are still a lot of items where P31 is not provided, or
>> > subclasses which have not been connected to "organization (Q43229)"…
>> >
>> > So in general, it's very hard to have any "guarantees that there are no
>> > duplicates", just because you don't have any guarantees that the
>> > information currently in Wikidata is complete or correct.
>> >
>> > I would recommend trying to import something a bit smaller to get
>> > acquainted with how Wikidata works and what the matching process looks
>> > like in practice. And beyond a one-off import, as Ettore said it is
>> > important to think how the data will be maintained in the future…
>> >
>> > Antonin
>> >
>> > On 16/10/2017 13:46, Ettore RIZZA wrote:
>> >>     - Wikidata has 40k organisations:
>> >>
>> >>     https://query.wikidata.org/#SELECT
>> >>     <https://query.wikidata.org/#SELECT> %3Fitem %3FitemLabel %0AWHERE
>> >>     %0A{%0A %3Fitem wdt%3AP31 wd%3AQ43229.%0A SERVICE wikibase%3Alabel
>> {
>> >>     bd%3AserviceParam wikibase%3Alanguage "[AUTO_LANGUAGE]%2Cen". }%0A}
>> >>
>> >>
>> >> Hi,
>> >>
>> >> I think Wikidata contains many more organizations than that. If we
>> >> choose the "instance of Business enterprise", we get 135570 results.
>> And
>> >> I imagine there are many other categories that bring together
>> commercial
>> >> companies.
>> >>
>> >>
>> >> https://query.wikidata.org/#SELECT%20%3Fitem%20%3FitemLabel%
>> 20WHERE%20%7B%0A%20%20%3Fitem%20wdt%3AP31%20wd%3AQ4830453.%
>> 0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AservicePa
>> ram%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%7D
>> >>
>> >> On the substance, the project to add all companies of a country would
>> >> make Wikidata a kind of totally free clone of Open Corporates
>> >> <https://opencorporates.com/>. I would of course be delighted to see
>> >> that, but is it not a challenge to maintain such a database? Companies
>> >> are like humans, it appears and disappears every day.
>> >>
>> >>
>> >>
>> >> 2017-10-16 13:41 GMT+02:00 Sebastian Hellmann
>> >> <[email protected]
>> >> <mailto:[email protected]>>:
>> >>
>> >>     Hi all,
>> >>
>> >>     the technical challenges are not so difficult.
>> >>
>> >>     - 2.2 million are the exact number of German organisations, i.e.
>> >>     associations and companies. They are also unique.
>> >>
>> >>     - Wikidata has 40k organisations:
>> >>
>> >>     https://query.wikidata.org/#SELECT
>> >>     <https://query.wikidata.org/#SELECT> %3Fitem %3FitemLabel %0AWHERE
>> >>     %0A{%0A %3Fitem wdt%3AP31 wd%3AQ43229.%0A SERVICE wikibase%3Alabel
>> {
>> >>     bd%3AserviceParam wikibase%3Alanguage "[AUTO_LANGUAGE]%2Cen". }%0A}
>> >>
>> >>     so there would be a maximum of 40k duplicates These are easy to
>> find
>> >>     and deduplicate
>> >>
>> >>     - The crawl can be done easily, a colleague has done so before.
>> >>
>> >>
>> >>     The issues here are:
>> >>
>> >>     - Do you want to upload the data in Wikidata? It would be a real
>> big
>> >>     extension. Can I go ahead
>> >>
>> >>     - If the data were available externally as structured data under
>> >>     open license, I would probably not suggest loading it into
>> wikidata,
>> >>     as the data can be retrieved from the official source directly,
>> >>     however, here this data will not be published in a decent format.
>> >>
>> >>     I thought that the way data is copied from coyrighted sources, i.e.
>> >>     only facts is ok for wikidata. This done in a lot of places, I
>> >>     guess. Same for Wikipedia, i.e. News articles and copyrighted books
>> >>     are referenced. So Wikimedia or the Wikimedia community are experts
>> >>     on this.
>> >>
>> >>     All the best,
>> >>
>> >>     Sebastian
>> >>
>> >>
>> >>     On 16.10.2017 10:18, Neubert, Joachim wrote:
>> >>>
>> >>>     Hi Sebastian,____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     This is huge! It will cover almost all currently existing German
>> >>>     companies. Many of these will have similar names, so preparing for
>> >>>     disambiguation is a concern.____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     A good way for such an approach would be proposing a property for
>> >>>     an external identifier, loading the data into Mix-n-match,
>> >>>     creating links for companies already in Wikidata, and adding the
>> >>>     rest (or perhaps only parts of them - I’m not sure if having all
>> >>>     of them in Wikidata makes sense, but that’s another discussion),
>> >>>     preferably with location and/or sector of trade in the description
>> >>>     field.____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     I’ve tried to figure out what could be used as key for a external
>> >>>     identifier property. However, it looks like the registry does not
>> >>>     offer any (persistent) URL to its entries. So for looking up a
>> >>>     company, apparently there are two options:____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     -          conducting an extended search for the exact string “A&A
>> >>>     Dienstleistungsgesellschaft mbH“____
>> >>>
>> >>>     -          copying the register number “32853” plus selecting the
>> >>>     court (Leipzig) from the according dropdown list and search
>> that____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     Both ways are not very intuitive, even if we can provide a link to
>> >>>     the search form. This would make a weak connection to the source
>> >>>     of information. Much more important, it makes disambiguation in
>> >>>     Mix-n-match difficult. This applies for the preparation of your
>> >>>     initial load (you would not want to create duplicates). But much
>> >>>     more so for everybody else who wants to match his or her data
>> >>>     later on. Being forced to search for entries manually in a
>> >>>     cumbersome way for disambiguation of a new, possibly large and
>> >>>     rich dataset is, in my eyes, not something we want to impose on
>> >>>     future contributors. And often, the free information they find in
>> >>>     the registry (formal name, register number, legal form, address)
>> >>>     will not easily match with the information they have (common name,
>> >>>     location, perhaps founding date, and most important sector of
>> >>>     trade), so disambiguation may still be difficult.____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     Have you checked which parts of the accessible information as
>> >>>     below can be crawled and added legally to external databases such
>> >>>     as Wikidata?____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     Cheers, Joachim____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     --____
>> >>>
>> >>>     Joachim Neubert____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     ZBW – German National Library of Economics____
>> >>>
>> >>>     Leibniz Information Centre for Economics____
>> >>>
>> >>>     Neuer Jungfernstieg 21
>> >>>     20354 Hamburg____
>> >>>
>> >>>     Phone +49-42834-462____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     __ __
>> >>>
>> >>>     __ __
>> >>>
>> >>>     *Von:*Wikidata [mailto:[email protected]
>> >>>     <mailto:[email protected]>] *Im Auftrag von
>> >>>     *Sebastian Hellmann
>> >>>     *Gesendet:* Sonntag, 15. Oktober 2017 09:45
>> >>>     *An:* [email protected]
>> >>>     <mailto:[email protected]>
>> >>>     *Betreff:* [Wikidata] Kickstartet: Adding 2.2 million German
>> >>>     organisations to Wikidata____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     Hi all,____
>> >>>
>> >>>     the German business registry contains roughly 2.2 million
>> >>>     organisations. Some information is paid, but other is public, i.e.
>> >>>     the info you are searching for at and clicking on UT (see example
>> >>>     below):____
>> >>>
>> >>>     https://www.handelsregister.de/rp_web/mask.do?Typ=e
>> >>>     <https://www.handelsregister.de/rp_web/mask.do?Typ=e>____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     I would like to add this to Wikidata, either by crawling or by
>> >>>     raising money to use crowdsourcing concepts like crowdflour or
>> >>>     amazon turk. ____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     It should meet notability criteria 2:
>> >>>     https://www.wikidata.org/wiki/Wikidata:Notability
>> >>>     <https://www.wikidata.org/wiki/Wikidata:Notability>____
>> >>>
>> >>>         2. It refers to an instance of a *clearly identifiable
>> >>>         conceptual or material entity*. The entity must be notable, in
>> >>>         the sense that it *can be described using serious and publicly
>> >>>         available references*. If there is no item about you yet, you
>> >>>         are probably not notable.____
>> >>>
>> >>>
>> >>>     The reference is the official German business registry, which is
>> >>>     serious and public. Orgs are also per definition clearly
>> >>>     identifiable legal entities.
>> >>>
>> >>>     How can I get clearance to proceed on this?
>> >>>
>> >>>     All the best,
>> >>>     Sebastian____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     __ __
>> >>>
>> >>>
>> >>>           Entity data____
>> >>>
>> >>>     __ __
>> >>>
>> >>>     Saxony District court *Leipzig HRB 32853 * – A&A
>> >>>     Dienstleistungsgesellschaft mbH ____
>> >>>
>> >>>     Legal status:____
>> >>>
>> >>>
>> >>>
>> >>>     Gesellschaft mit beschränkter Haftung  ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     Capital:____
>> >>>
>> >>>
>> >>>
>> >>>     25.000,00 EUR ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     Date of entry:____
>> >>>
>> >>>
>> >>>
>> >>>     29/08/2016
>> >>>     (When entering date of entry, wrong data input can occur due to
>> >>>     system failures!) ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     Date of removal:____
>> >>>
>> >>>
>> >>>
>> >>>     - ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     Balance sheet available: ____
>> >>>
>> >>>
>> >>>
>> >>>     - ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     Address (subject to correction):____
>> >>>
>> >>>
>> >>>
>> >>>     A&A Dienstleistungsgesellschaft mbH
>> >>>     Prager Straße 38-40____
>> >>>
>> >>>     04317 Leipzig ____
>> >>>
>> >>>
>> >>>
>> >>>
>> >>>     __ __
>> >>>
>> >>>     --
>> >>>     All the best,
>> >>>     Sebastian Hellmann
>> >>>
>> >>>     Director of Knowledge Integration and Linked Data Technologies
>> >>>     (KILT) Competence Center
>> >>>     at the Institute for Applied Informatics (InfAI) at Leipzig
>> University
>> >>>     Executive Director of the DBpedia Association
>> >>>     Projects: http://dbpedia.org, http://nlp2rdf.org,
>> >>>     http://linguistics.okfn.org, https://www.w3.org/community/ld4lt
>> >>>     <http://www.w3.org/community/ld4lt>
>> >>>     Homepage: http://aksw.org/SebastianHellmann
>> >>>     <http://aksw.org/SebastianHellmann>
>> >>>     Research Group: http://aksw.org____
>> >>>
>> >>>
>> >>>
>> >>>     _______________________________________________
>> >>>     Wikidata mailing list
>> >>>     [email protected] <mailto:[email protected]
>> >
>> >>>     https://lists.wikimedia.org/mailman/listinfo/wikidata
>> >>>     <https://lists.wikimedia.org/mailman/listinfo/wikidata>
>> >>
>> >>     --
>> >>     All the best,
>> >>     Sebastian Hellmann
>> >>
>> >>     Director of Knowledge Integration and Linked Data Technologies
>> >>     (KILT) Competence Center
>> >>     at the Institute for Applied Informatics (InfAI) at Leipzig
>> University
>> >>     Executive Director of the DBpedia Association
>> >>     Projects: http://dbpedia.org, http://nlp2rdf.org,
>> >>     http://linguistics.okfn.org, https://www.w3.org/community/ld4lt
>> >>     <http://www.w3.org/community/ld4lt>
>> >>     Homepage: http://aksw.org/SebastianHellmann
>> >>     <http://aksw.org/SebastianHellmann>
>> >>     Research Group: http://aksw.org
>> >>
>> >>     _______________________________________________
>> >>     Wikidata mailing list
>> >>     [email protected] <mailto:[email protected]>
>> >>     https://lists.wikimedia.org/mailman/listinfo/wikidata
>> >>     <https://lists.wikimedia.org/mailman/listinfo/wikidata>
>> >>
>> >>
>> >>
>> >>
>> >> _______________________________________________
>> >> Wikidata mailing list
>> >> [email protected]
>> >> https://lists.wikimedia.org/mailman/listinfo/wikidata
>> >>
>> >
>> >
>> > _______________________________________________
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>> > [email protected]
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>> >
>>
>>
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