  Distinguishing lexical relations has been a long term pursuit in natural
language processing (NLP) domain. Recently, in order to detect lexical
relations like hypernymy, meronymy, co-hyponymy etc., distributional semantic
models are being used extensively in some form or the other. Even though a lot
of efforts have been made for detecting hypernymy relation, the problem of
co-hyponymy detection has been rarely investigated. In this paper, we are
proposing a novel supervised model where various network measures have been
utilized to identify co-hyponymy relation with high accuracy performing better
or at par with the state-of-the-art models.
