Last Friday saw the release of the Wikilinks Corpus from Research at Google, 40 million entities in context strong.

As explained in a blog post by Dave Orr, Amar Subramanya, and Fernando Pereira at Google Research, the Big Data set “involves 40 million total disambiguated mentions within over 10 million web pages — over 100 times bigger than the next largest corpus.” The mentions, the post relates, are found by looking for links to Wikipedia pages where the anchor text of the link closely matches the title of the target Wikipedia page. If each page on Wikipedia is throught of as an entity, then the anchor text can be thought of as a mention of the corresponding entity, it says.

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Valentin Spitkovsky and Peter Norvig of the Google Research Team have posted an article about their new paper on dictionaries for linking text, entities, and ideas. They write, “Human language is both rich and ambiguous. When we hear or read words, we resolve meanings to mental representations, for example recognizing and linking names to the intended persons, locations or organizations. Bridging words and meaning — from turning search queries into relevant results to suggesting targeted keywords for advertisers — is also Google’s core competency, and important for many other tasks in information retrieval and natural language processing. We are happy to release a resource, spanning 7,560,141 concepts and 175,100,788 unique text strings, that we hope will help everyone working in these areas.” Read more

Sebastian Thrun and Peter Norvig are teaching an online course entitled Introduction to Artificial Intelligence from September 26 through December 16, 2011. The course, also taught in-class at Stanford University, is a popular intro level examination of AI. “For the online version,” the description states, “the instructors aim to offer identical materials, assignments, and exams, and to use the same grading criteria. Both instructors will be available for online discussions.” Read more