And then there is today's automated

　　translation technology.Services like Google Translate can provide the main idea of a passage of a text.Computers learn to translate by searching for correlations in texts that have been translated by humans.But if you're a newspaper publisher seeking foreign readers or an expert wanting to educate speakers of another language，human translation remains the only option.

　　Martin Benjamin wants to change that.His attempt is called Kamusi and it's a multilingual dictionary that contains all the world's languages.Unlike

　　other online dictionaries, Kamusi is built around concepts as well as words.So the word“spring”，

　　for

　　instance，is linked to

　　several

　　concepts，including the season that comes before summer and a sudden upward or forward motion.

　　This structure could solve one of the biggest challenges for machine translation.Asked to translate “spring in her step” into French，for example，Google chooses printemps—the season—for “spring”．The inability of computers to deal with homonyms—words that are spelled the same but have different meanings—is one reason why machine translations are often

　　so misrepresented.Kamusi avoids this problem by recognizing that “spring” is associated with multiple concepts and prompting the user to say which is relevant.

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