![]() Now if you upgrade again for your 6th month, and we generate entries you’ll then receive 21 entries. If we generate entries for a promotion you’ll receive 5 entries. How the system generates entries are based on 2 factors:Ģ= The highest tier you are on, at the time of generating entriesįor example, if you are on premium for 4 months that is 16 entries, then you drop down to the entry-level for your 5th month. If a Loyalty Member decides to downgrade their membership, that comes into effect on the next billing cycle and if we generate a new promotion you’ll receive access and entries based on that tier. If we generate a new promotion you will receive entries for that tier. Once that comes to effect you will receive the amount of entries and access associated with that membership tier. If a LMCT+ Loyalty Member decides to upgrade their membership, that will come into effect on your next billing cycle. About 8000 violations are listed here, and clicking on one shows a case where a person is missing the statement "is a: person".What happens if i upgrade/downgrade my membership? So the property "awards received" requires the object to be a person/creative work/organisation/etc. ![]() Violations of these constraints are marked with (!) on the item's page, and also in various lists. Properties also have numerous constraints, such as required dates of birth and death to be in the past, requiring objects for a "citizenship" property to be people, and so on. Share Cite Follow edited at 20:49 answered at 20:44 Old John 19. Related edits by the same user are also combined into "editgroups", and this page shows recent ones. Thus there are exactly 99 pairs satisfying the relation, and hence exactly 99 entries in the matrix which are 1, and then 100 2 99 9901 entries which are zero. That’s about the size of a squared-off iPod touch, and although it’s twice as thick. Designed by Thomas Meyerhoffer, a former Apple designer, the WikiReader measures 3.9 inches (9.9 cm) square and 0.8 inches (20 mm) thick, and weighs in at 4.5 ounces (127 g). There is also an AI system (the same as on en.) that predicts bad-faith and low-quality edits, which are tagged as such, highlighted in changes, and available in filters. The concept is simple embed all of Wikipedia in an inexpensive handheld device. The overview of recent pages draws attentions to any change, as does the ability to add items to your personal watchlist. (Edit, to answer a question from the comments:) Quality-control of bot data is generally identical to other edits, except that bot edits (and similar, such as those using QuickStatement) are tagged as such. Most recently, the English Wikipedia has decided to do use some home-grown method of managing short page discriptions, for example. When that happens, either someone continues syncing it at least in one direction. And because each individual project has a lot of freedom in such matters, some have moved away from using Wikidata as their backend for storing structured information, and are doing their own thing. But most of the data comes from other public dataset.įor reasons beyond my understanding, relations between some wikipedias and wikidata aren't always perfect. Imports from Wikipedia provide a lot of the structure, because every page gets its wikidata item (and only one). The computational biology community, for example, does use Wikidata as a sort of hub in this form. ![]() If you weigh by importance/number of views, humans are probably ahead.Ī group you didn't mention, but that might the significant, is "in between": people using either OpenRefine or QuickStatements to semi-manually match ("reconcile") some external dataset and import it. If you measure just by "number of statements", bots probably add the majority of data. ![]() When you check the "recent changes" (and deactivate the "only humans" filter), or the history of any specific page/item, the bots are marked with a little 'b', and their names also end on ".Bot".
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