import pickle
import sys
from math import log
import regex as re

def count_prob(bigrams, unigrams):
    prob = (bigrams + 1.0) / (unigrams + 1)
    if prob > 1.0:
        return 1.0
    else:
        return prob

def main():
    ngrams = pickle.load(open('ngrams_2.pkl', 'rb'))
    vocabulary_size = len(ngrams[1])
    for line in sys.stdin:
        words = re.findall(r'.*\t.*\t.* (.*?)\t(.*?) ', line.lower())[0]
        #print(words)
        left_word = [str(words[0])]
        right_word = [str(words[1])]

        probabilities = []
        for word in ngrams[1].keys():
            word = str(word[0])
            pre_ngram = tuple(left_word + [word])
            post_ngram = tuple([word] + right_word)
            #print(pre_ngram)
            pre_ngram_prob = count_prob(ngrams[2].get(pre_ngram, 0), ngrams[1].get(word[0],0) + vocabulary_size * 1000)
            #if pre_ngram_prob>0:
            post_ngram_prob = count_prob(ngrams[2].get(post_ngram, 0), ngrams[1].get(word[0],0) + vocabulary_size * 1000)

            probabilities.append((word, pre_ngram_prob * post_ngram_prob))
        probabilities = sorted(probabilities, key=lambda t: t[1], reverse=True)[:50]
        probability = 1.0
        text = ''
        counter = 0
        has_log_prob0 = False
        for p in probabilities:
            word = p[0]
            prob = p[1]
            if counter == 0 and (probability - prob <= 0.0):
                text = word + ':' + str(log(0.95)) + ' :' + str(log(0.05))
                has_log_prob0 = True
                break
            if counter > 0 and (probability - prob <= 0.0):
                text += ':' + str(log(probability))
                has_log_prob0 = True
                break
            text += word + ':' + str(log(prob)) + ' '
            probability -= prob
            counter += 1
        if not has_log_prob0:
            text += ':' + str(log(0.0001))
        print(text)


if __name__ == '__main__':
    main()