With the tremendous growth of Google’s Knowledge Graph, tripling in size, CNET reports on Google’s plan to extend it into other languages and the challenges it faces.

The project to make Knowledge Graph content available in so many new languages simultaneously was no small feat. Even in English, creating an easily searchable database of relationships is fraught with potential problems. If I search for “giants,” do I mean the baseball team, the football team, or enormous people? Using a variety of signals, Google makes its best guess — and then presents its findings in a handy panel on the right-hand side of the results page. (Or it will display a panel asking if you want results for baseball or football.) Now imagine running that same query in other languages. What does a user searching for “giants” in French want? How about in Italian? Japanese? The task of localizing Google’s knowledge graph fell in part to Tamar Yehoshua, who oversees Google’s efforts to take search international. What roadblocks has Google found along the way? Here are a few. Figuring out where you are. This challenge predates the Knowledge Graph, but determining a user’s location is still the foundation of all localization. The most important signal is the Google domain you’re using — .com indicates the United States, .co.jp indicates Japan, and so on. From there. Google looks at your IP address, the language of your browser, and the language you’re searching in. The idea is to drill down to your current city so that results are as local as possible. (Using the settings page, users can search as if they were in another city.) This has a big impact on search results. Search “UPC” on Google.com and you’ll see information about universal product codes. But take the same search to Google.ie, the company’s Irish domain, and the query brings up results for UPC Ireland — the biggest cable television provider in that country. Making answers locally relevant. Knowing where users are is only the first step. From there Google has to consider what sorts of things other people in that location tend to search for, and offer results accordingly. This is perhaps the Knowledge Graph’s biggest challenge as it expands around the globe, because a query that Google can answer well in English might not be useful in another country. Getting it right means more than performing a basic translation. Read the full article.