R. Apriori. Preprocess data to know the name of the attributes in the rules

Question

I am using the dataset "adult". http://archive.ics.uci.edu/ml/datasets/Adult I have retrieved frequent rules using apriori and sorted them by lift.

library(arules)
trans = read.transactions("adult.data", format = "basket", sep = ",", rm.duplicates = TRUE)
rules <- apriori(trans)
rules.lift <- sort(rules, decreasing = TRUE, by="lift")

When I execute

  inspect(head(rules.lift,100))

I obtain the following:

    lhs                 rhs               support confidence     lift
  1   { 13,                                                            
      Male,                                                          
      United-States} => { Bachelors}    0.1024507  0.9976077 6.066125
  2   { 0,                                                             
       13,                                                            
       Male,                                                          
       United-States} => { Bachelors}    0.1024507  0.9976077 6.066125

ETC

For example, in the rule:

 { 0,                                                             
   13,                                                            
   Male,                                                          
   United-States} => { Bachelors}

How can I know which attribute that 0 and that 13 are? I have looked at the description of the data set and to the data itself so I guess that 13 is the education-num and 0 is the capital-loss but sometimes two or more attributes can have the same ranges so I would not know how to distinguish them.

>class(rules.lift)
[1] "rules"
attr(,"package")
[1] "arules"

I've read here: How could we know the ColumnName /attribute of items generated in Rules that the problem is I haven't preprocessed the data. So, how can I do that?

Thank you very much!