# Enter your code here. Read input from STDIN. Print output to STDOUT

import sys
import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier

data = []
for line in sys.stdin:
    
    l = [i for i in line.split()]
    data.append(l)
    
#print(data)

num = int(data[0][0])
param = int(data[0][1])
q = int(data[num+1][0])

#print(num,param,q)

X = np.array(data[1:num])
X_train = []
y_train = []

for i in X:
    
    X_train.append(i[2:])
    y_train.append(int(i[1]))
l = []
temp = []
for j in X_train:
    l = []
    for i in j:
        
        t = i.split(":")
        l.append(float(t[1]))
    temp.append(l)

X_train = np.array(temp)
#print(X_train)
y_train = np.array(y_train)
X_t = np.array(data[num+2:])

X_test = []
for i in X_t:
   
    X_test.append(i[1:])
    
temp = []
l1 = []
for j in X_test:
    l1 = []
    for i in j:
        
        t1 = i.split(":")
        l1.append(float(t1[1]))
    temp.append(l1)
    
X_test = np.array(temp)
#print(X_test)
#print(X_train.shape,y_train.shape,X_test.shape)

rfc = RandomForestClassifier()

clf = rfc.fit(X_train,y_train)

predict = clf.predict(X_test)

for i in range(len(predict)):
    
    if predict[i]>0:
        
        print(X_t[i][0],"+1")
        
    else:
        print(X_t[i][0],"-1")