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Bob Roberts is in charge of performing translations of documents between various languages. To aid him in this endeavor his bosses have provided him with translation files. These files come in twos — one containing sample phrases in one of the languages and the other containing their translations into the other language. However, some over-zealous underling, attempting to curry favor with the higher-ups with his initiative, decided to alphabetically sort the contents of all of the files, losing the connections between the phrases and their translations. Fortunately, the lists are comprehensive enough that the original translations can be reconstructed from these sorted lists. Bob has found this is most usually the case when the phrases all consist of two words. For example, given the following two lists:
Language 1 Phrases Language 2 Phrases
Bob is able to determine that arlo means hot, zym means seat, flub means school, pleve means bus, and dourm means stop. After doing several of these reconstructions by hand, Bob has decided to automate the process. And if Bob can do it, then so can you.
Input will consist of multiple input sets. Each input set starts with a positive integer n <= 250, indicating the number of two-word phrases in each language. This is followed by 2n lines, each containing one two-word phrase: the first n lines are an alphabetical list of phrases in the first language, and the remaining n lines are an alphabetical list of their translations into the second language. Only upper and lower case alphabetic characters are used in the words. No input set will involve more than 25 distinct words. No word appears as the first word in more than 10 phrases for any given language; likewise, no word appears as the last word in more than 10 phrases. A line containing a single 0 follows the last problem instance, indicating end of input.
For each input set, output lines of the form
where word1 is a word in the first language and word2 is the translation of word1 into the second language, and a slash separates the two. The output lines should be sorted according to the first language words, and every first language word should occur exactly once. There should be no white space in the output, apart from a single blank line separating the outputs from different input sets. Imitate the format of the sample output, below. There is guaranteed to be a unique correct translation corresponding to each input instance.
4 arlo zym flub pleve pleve dourm pleve zym bus seat bus stop hot seat school bus 2 iv otas otas re ec t eg ec 0
arlo/hot dourm/stop flub/school pleve/bus zym/seat iv/eg otas/ec re/t
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