In this paper we present KX, a system for key-phrase extraction developed at FBK-IRST, which exploits basic linguistic annotation combined with simple statistical measures to select a list of weighted keywords from a document. The system is flexible in that it offers to the user the possibility of setting parameters such as frequency thresholds for collocation extraction and indicators for key-phrase relevance, as well as it allows for domain adaptation exploiting a corpus of documents in an unsupervised way. KX is also easily adaptable to new languages in that it requires only a PoS-Tagger to derive lexical patterns. In the SemEval task 5 "Automatic Key-phrase Extraction from Scientific Articles", KX performance achieved satisfactory results both in finding reader-assigned keywords and in the combined keywords subtask.
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