n, k, m = map(int, input().split())

train = []
test = []
output = []


def k_nearest(dif):
    tmp = []
    while len(dif) > k:
        dif.sort()
        tmp = dif.pop()
    nearest = [0 for i in range(n)]
    for i in range(len(dif)):
        nearest[dif[i][1]] += 1
    if nearest.count(max(nearest)) > 1:
        nearest[tmp[1]] += 1
    return nearest.index(max(nearest))


def classify(weight, height):
    dif = []
    for j in range(len(train)):
        dif.append(max(abs(weight - train[j][1]), abs(height - train[j][2])), train[j][0])
    index = k_nearest(dif)
    train.append([index, weight, height])
    train.sort()
    output.append(index)


for i in range(n):
    w, h = map(int, input().split())
    train.append([i, w, h])

for i in range(m):
    w, h = map(int, input().split())
    test.append([w, h])

for i in range(m):
    classify(test[i][0], test[i][1])

s = ''
for x in output:
    s += str(x + 1) + ' '
s = s.strip()
print(s)