From Words to Concepts and Back: Dictionaries for Linking Text, Entities and Ideas by Valentin Spitkovsky and Peter Norvig (Google Research Team).
From the post:
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.
How do we represent concepts? Our approach piggybacks on the unique titles of entries from an encyclopedia, which are mostly proper and common noun phrases. We consider each individual Wikipedia article as representing a concept (an entity or an idea), identified by its URL. Text strings that refer to concepts were collected using the publicly available hypertext of anchors (the text you click on in a web link) that point to each Wikipedia page, thus drawing on the vast link structure of the web. For every English article we harvested the strings associated with its incoming hyperlinks from the rest of Wikipedia, the greater web, and also anchors of parallel, non-English Wikipedia pages. Our dictionaries are cross-lingual, and any concept deemed too fine can be broadened to a desired level of generality using Wikipedia’s groupings of articles into hierarchical categories.
The database that we are providing was designed for recall. It is large and noisy, incorporating 297,073,139 distinct string-concept pairs, aggregated over 3,152,091,432 individual links, many of them referencing non-existent articles. For technical details, see our paper (to be presented at LREC 2012) and the README file accompanying the data. (emphasis added)
Did you catch those numbers?
Now there is a truly remarkable resource.
What will you make out of it?