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...
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 <hellmann@informatik.uni-leipzig.de mailto:hellmann@informatik.uni-leipzig.de>:
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:wikidata-bounces@lists.wikimedia.org <mailto:wikidata-bounces@lists.wikimedia.org>] *Im Auftrag von *Sebastian Hellmann *Gesendet:* Sonntag, 15. Oktober 2017 09:45 *An:* wikidata@lists.wikimedia.org <mailto:wikidata@lists.wikimedia.org> *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 Wikidata@lists.wikimedia.org <mailto:Wikidata@lists.wikimedia.org> 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 Wikidata@lists.wikimedia.org <mailto:Wikidata@lists.wikimedia.org> https://lists.wikimedia.org/mailman/listinfo/wikidata <https://lists.wikimedia.org/mailman/listinfo/wikidata>
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