PSL Users

Email: globalpsyche...@gmail.com https://globalpsychedelicsonline.com/product/buy-pure-

Please try to limit duplicate threads to a single communication channel. We'll debug this on the

Hey Xue Wen, PSL will use as many threads as the jvm has access to. Specifically during parts of

Hi Xue Wen, Yes, you are correct that your error is the same as in the thread you linked. I will add

Hey Xue Wen, It looks like you may have duplicate data in your father predicate. I can't tell

Hey Shirel, This sounds like a really interesting use case. I hope I can answer all your questions. 1

According to what I said earlier... Remember that your last email before today was 5 months ago, so

Hey Mayra , So sorry I missed this question (it didn't go to my inbox). If you want to access

Interesting, thanks for the info. I put in a fix that is going through CI now: https://github.com/

Thank you Eriq for the clarification, very helpful! Eriq Augustine schrieb am Freitag, 29. Oktober

You are right, PSL version 2.0.0 does still have support for LTN. Since LTN is a weight learning

Setting a negative prior solved the issue right away. Thanks for all the help! On Monday, January 4,

Hello, Greetings..!. Setting up a hassle free work environment is what makes the Company beneficial.

That was an elaborate explanation! Thanks a ton! On Wednesday, November 11, 2020 at 10:13:00 AM UTC+5

Hey Jonathan, Each running instance of PSL will want a lock on it's database and try to use all

Hey, Efficiently and simultaneously learning an external model's parameters and weights in PSL is

Hey Jerry, I have three different recommendations for performance depending on how large you expect

Can you give some more info? What interface are you using? What command are you using to run PSL?

Thanks Eriq. I found it here https://github.com/linqs/kgi_musicbrainz/blob/master/data/

Hey Nouf, We have talked about this before. PSL will arbitrarily choose on of the solutions. -eriq On

Non-observed atoms from open predicates can take several different initial values depending on the

Hey Shashi, 1. Why does some observation have weights ? In PSL, we use the term "weight"

Hey, We can take your rule and convert it into disjunctive normal form: !Predicate2(X,Y) -> !

Hey, The short answer is yes, you should explicitly specify all your inference targets. This thread

observed_fact(A) & inferred_fact(A) -> conclusive_inference(A) !observed_fact(A) || !

The full rule set is: 1: !infered_similarity(A)^2 1: !infered_name_similarity(A)^2 100:

Hey Tzahi, Just looking at this real quick, it seems to me like you need the "confidences"

Looks like inference is based on MLN. On Friday, May 3, 2019 at 9:15:18 AM UTC-4, zachary...@gmail.

No, you should give them a weight. You usually give them a smaller weight then the rest of your rules

Hi Tzahi, This an interesting problem, thanks for sharing. Here is how I would write the rules: