We use search engine results to address a particularly dif?cult cross-domain
language processing task, the adaptation of named entity recognition (NER) from
news text to web queries. The key novelty of the method is that we submit a token
with context to a search engine and use similar contexts in the search results as
additional information for correctly classifying the token. We achieve strong gains
in NER performance on news, in-domain and out-of-domain, and on web queries.