  The project aims to provide a semi-supervised approach to identify Multiword
Expressions in a multilingual context consisting of English and most of the
major Indian languages. Multiword expressions are a group of words which refers
to some conventional or regional way of saying things. If they are literally
translated from one language to another the expression will lose its inherent
meaning.
  To automatically extract multiword expressions from a corpus, an extraction
pipeline have been constructed which consist of a combination of rule based and
statistical approaches. There are several types of multiword expressions which
differ from each other widely by construction. We employ different methods to
detect different types of multiword expressions. Given a POS tagged corpus in
English or any Indian language the system initially applies some regular
expression filters to narrow down the search space to certain patterns (like,
reduplication, partial reduplication, compound nouns, compound verbs, conjunct
verbs etc.). The word sequences matching the required pattern are subjected to
a series of linguistic tests which include verb filtering, named entity
filtering and hyphenation filtering test to exclude false positives. The
candidates are then checked for semantic relationships among themselves (using
Wordnet). In order to detect partial reduplication we make use of Wordnet as a
lexical database as well as a tool for lemmatising. We detect complex
predicates by investigating the features of the constituent words. Statistical
methods are applied to detect collocations. Finally, lexicographers examine the
list of automatically extracted candidates to validate whether they are true
multiword expressions or not and add them to the multiword dictionary
accordingly.
