James Fletcher

Looks like you're right! Yes please do submit PR(s) to fix the issues you see!

Hi @nicolamassarenti, The issue I've noticed here is that KGLIB has not yet been updated to use the latest version of Grakn. The latest release of KGLIB works with Grakn...

> Do you have any ETA about the delivery of `kglib` version compatible with Grakn 2.0.x? We should do this in the coming days to unblock users such as yourself!...

Hi @nicolamassarenti, thanks for trying, but yes I suggest it's best to wait for the next release :/ We'll try to make that happen soon!

I believe we've tried with both Python 3.6.x and 3.7.x for which it's working fine @PolKul!

Hi @nicolamassarenti I have a [branch that's compatible](https://github.com/jmsfltchr/kglib/tree/typedb-upgrade), but we still have a bug to iron out before we can release. You may be able to depend on my branch...

Hi! Not presently out of the box, but if you can design a metric to determine the loss in an unsupervised setting then it's possible with this framework. One measure...

~~Yes that's right! @Qbbz could you copy this issue over to [graknlabs/kglib](https://github.com/graknlabs/kglib) please?~~

Thanks for the feature request! In the link you provided I see that you can define a polygon, a 2xN dimensional array to hold coordinates. To give us a better...

I've separately encountered the same error from another scenario in recursion: `Scenario: when relations' and attributes' inferences are mutually recursive, the inferred concepts can be retrieved`: ``` java.lang.AssertionError com.vaticle.typedb.core.common.exception.TypeDBException: at...