Spence Green

I posted the final version of our NAACL 2012 paper on entity clustering across languages. The idea is to identify text mentions to entities in the world (e.g., people, places, and things) in multiple languages. We’ve tried to stay away from language-specific feature engineering. Moreover, we only used training resources that are abundant for many languages. For example, we make use of the topical structure of Wikipedia in which a single topic (e.g., “Steve Jobs”) is discussed in many languages. Our techniques should be especially useful for low-resource languages.

We wrote the first few lines of code for this project in June 2010. The code for this paper now exceeds 20k lines and I shudder to think of the rolling brownouts our experiments have likely caused throughout Maryland. We’ve burned up the COE computing cluster. I am thankful that this work will finally receive a public hearing.

Names are fascinating objects. They tend to originate in one language, usually the language of the culture in which the entity originates. Then the name spreads. Nicknames and aliases develop.  New variants arise in other languages and writing systems. We’ve started to think of this phenomenon as a phylogenetic process, much like the proliferation of linguistic cognates or even bird species. Nick and Jason have been developing a model for this process, an initial version of which they recently presented at the NIPS NP Bayes workshop.