import pickle
import sys
from math import log

import regex as re


def get_prob(count, total, classes):
    prob = (count + 1.0) / (total + classes)
    if prob > 1.0:
        return 1.0
    else:
        return prob


def main():
    ngrams = pickle.load(open('ngrams.pkl', 'rb'))
    vocabulary_size = len(ngrams[1])
    for line in sys.stdin:
        words = re.findall(r'.*\t.*\t.* (.*?) (.*?)\t(.*?) (.*?) ', line.lower())[0]
        left_words = [str(words[0]), str(words[1])]
        right_words = [str(words[2]), str(words[3])]

        probabilities = []
        for word in ngrams[1].keys():
            word = str(word[0])
            pre_ngram = tuple(left_words + [word])
            post_ngram = tuple([word] + right_words)
            pre_ngram_prob = get_prob(ngrams[3].get(pre_ngram, 0), ngrams[2].get(tuple(left_words), 0),
                                      vocabulary_size)
            post_ngram_prob = get_prob(ngrams[3].get(post_ngram, 0), ngrams[2].get(post_ngram[0:2], 0),
                                       vocabulary_size)
            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()