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    <p>I'm not aware of any ready to use open source libraries that implement the sort of <strong>clustering on demand</strong> of named entities provided by Google Sets. However, there are a few academic papers that describe in detail how to build similar systems, e.g.:</p> <ul> <li><p><a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.68.6493&amp;rep=rep1&amp;type=pdf" rel="nofollow noreferrer"><strong>Language-Independent Set Expansion of Named Entities using the Web</strong></a> <br/>Wang and Cohen, in EMNLP 2009 <br/> <a href="http://www.boowa.com/" rel="nofollow noreferrer">Online Demo</a> </p></li> <li><p><a href="http://www.gatsby.ucl.ac.uk/~heller/bsets.pdf" rel="nofollow noreferrer"><strong>Bayesian Sets</strong></a><br/> Ghahramani and Heller, in NIPS, 2005</p></li> </ul> <p>Below is a brief summary of Wang and Cohen's method. If you do end up implementing something like this yourself, it might be good to start with their method. I suspect most people will find it more intuitive than Ghahramani and Heller's formulation.</p> <p><strong>Wang and Cohen 2009</strong></p> <p>Wang and Cohen start by describing a method for automatically constructing <strong>extraction patterns</strong> that allow them to find lists of named entities in any sort of structured document. The method looks at the prefixes and suffixes bracketing known occurrences of named entities. These prefix and suffixes are then used to identify other named entities within the same document. </p> <p>To complete a clusters of entities, they <strong>build a graph</strong> consisting of the interconnections between named entities, the extraction patterns associated with them, and the documents. Using this graph and starting at the nodes for the cluster's seed entities (i.e., the initial set of entities in the set to be completed), they perform numerous <strong>random walks</strong> on the graph up to 10 steps in length. They count how many times they reach the nodes corresponding to non-seed entities. Non-seed entities with high counts can then be used to complete the cluster.</p>
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    1. COthanks a lot for the answer. Then, I guess I'll go with implementing it myself.
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      1. USNicolas M.
 

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