Update dictionary values dynamically and reduce cognitive complexity of my code

I tried to update the dictionary values but output is not as expected also i wanted to reduce the code complexity of the code. Could someone help me to reduce the cognitive complexity with optimized code.

def post_process_slot(query_split , predict_labels):
    # print(query_split)
    d = {
    "product" :[],
    "quantity" :[]
    }
    ls = []
    for i,j in zip(query_split,predict_label):
        if j == "0":
            continue
        elif j == "quantity":
            d["quantity"].append(i)
        elif j == "product":
            ls.append(i)
        d["product"].append(ls)

        elif j == "B-product":
            ls.append("-")
            ls.append(i)
        elif j == "I-product":
            ls.append(i)
            d["product"].append(ls)
    ls1  = d["product"][0]
    ls2 = " ".join((ls1))
    ls3 =ls2.split("-")
    ls3.remove("")
    d["product"] = ls3
    return d

    query = "i want to order 7 Mountain Dew Spark bottles and 5 pepsi"
    predict_label = ['O', 'O', 'O', 'O', 'quantity', 'B-product', 'I- 
    product', 'I- 
    product','0','O' , 'quantity','product']
    query_split = query.split(" ")
    result = post_process_slot(query_split , predict_label)
    print(result)

Expected output:
    {'product': ['Mountain Dew Spark','pepsi'], 'quantity': ['7', '5']}

    Actual output:
    {'product': [' Mountain Dew Spark  pepsi'], 'quantity': ['7', '5']}