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One of the most impressive human endeavors of the past two decades is thecollection and categorization of human knowledge in the free and accessibleformat that is Wikipedia. In this work we ask what makes a term worthy ofentering this edifice of knowledge, and having a page of its own in Wikipedia?To what extent is this a natural product of on-going human discourse anddiscussion rather than an idiosyncratic choice of Wikipedia editors?Specifically, we aim to identify such "wiki-worthy" terms in a massive newscorpus, and see if this can be done with no, or minimal, dependency on actualWikipedia entries. We suggest a five-step pipeline for doing so, providingbaseline results for all five, and the relevant datasets for benchmarking them.Our work sheds new light on the domain-specific Automatic Term Extractionproblem, with the problem at hand being a domain-independent variant of it.

What if we had no Wikipedia? Domain-independent Term Extraction from a Large News Corpus