Named Entities (NEs) that occur in natural language text are important especially due to the advent of social media, and they play a critical role in the development of many natural language technologies. In this paper, we systematically analyze the patterns of occurrence and co-occurrence of NEs in standard large English news corpora - providing valuable insight for the understanding of the corpus, and subsequently paving way for the development of technologies that rely critically on handling NEs. We use two distinctive approaches: normal statistical analysis that measure and report the occurrence patterns of NEs in terms of frequency, growth, etc., and a complex networks based analysis that measures the co-occurrence pattern in terms of connectivity, degree-distribution, small-world phenomenon, etc. Our analysis indicates that: (i) NEs form an open-set in corpora and grow linearly, (ii) presence of a kernel and peripheral NE's, with the large periphery occurring rarely, and (iii) a strong evidence of small-world phenomenon. Our findings may suggest effective ways for construction of NE lexicons to aid efficient development of several natural language technologies.

This position paper outlines our project – WikiBABEL – which will be released as an open source project for the creation of multilingual Wikipedia content, and has potential to produce parallel data as a by-product for Machine Translation systems research. We discuss its architecture, functionality and the user-experience components, and briefly present an analysis that emphasizes the resonance that the WikiBABEL design and the planned involvement with Wikipedia has with the open source communities in general and Wikipedians in particular.