categorical fixed effect with three levels

Question

I have a fixed effect with three levels and I used the following contrasts that created 2 columns in my data set

 data = data %>%
  mutate(contrast_B = ifelse(group == "A", -0.5,
                               ifelse(type == "B", 0.5, 0))) %>%
  mutate(contrast_C = ifelse(group == "A", -0.5,
                              ifelse(type == "C", 0.5, 0)))

I included them in my model along with other fixed effects which all are binary with two levels as follows.

model <-lmer(log(dependent variable) ~ contrast_B * contrast_C * 
   fixed effect * fixed effect * fixed effect + 
   (1|subject)+ (1|item), data = data....

But I got a message

fixed-effect model matrix is rank deficient so dropping 12 columns/coefficients"

Does anybody know how to fix it?